departmental plan for assessment of student learning€¦ · 2007-10-20 · these update of the...

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DEPARTMENTAL PLAN FOR ASSESSMENT OF STUDENT

LEARNING

EARTH SYSTEM SCIENCE AND POLICY

***REVISED – JANUARY 2015***

I. ESSP DEPARTMENT

ESSP Mission Statement

To provide an integrated and creative learning environment that fosters intellectual growth, critical thinking, and practical engagement in research and sustainable management of the Earth system and resources. Departmental Goals

To fulfill the mission, the overall goal is to promote sustainability by pursuing:

1. Excellence in learning through a student-structured curriculum, a multi-disciplinary teaching approach, and experiential learning environments.

2. Excellence in discovery through research driven by societal needs and values

and occurs within an Earth System Science paradigm.

3. Excellence in engagement through outreach, service, and practical experience, which put knowledge related to Earth System Science and Policy to work.

The overall Student learning outcomes for all graduate degree programs are:

1. A breadth of knowledge in Earth System Science and Policy and the ability to apply that knowledge to address societal-driven sustainability science research, with a broad sense of ethical and professional responsibilities.

2. A strong knowledge of multi-scale processes, cutting-edge computer technology, geographical information systems (GIS), remote sensing, and quantitative analysis.

3. A strong knowledge of environmental policy, and environmental and resource economics related to human-environment interactions.

4. Written and oral communication skills that will facilitate the transfer of knowledge to support actionable decisions.

5. The ability to function within multi-disciplinary teams to accomplish common goals.

6. An awareness of and preparation for a lifetime of learning.

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II. ESSP MASTER DEGREES

Master of Environmental Management – M.E.M.

The M.E.M. degree is a professional program which emphasizes practical experience especially through an internship. The goal of the M.E.M. degree program is to help the students develop the capabilities for a career in environmental management, sustainable development, or environmental policy. In conjunction with the six overall learning outcomes for the department, the M.E.M. students are able to:

1. Implement their knowledge into practical applications especially through a successful internship experience.

2. Holistically apply particular learned skill sets and acquire additional skills needed for development of a desired professional career path.

Master of Science – M.S.

The M.S. degree is a research oriented program which involves conducting a research project culminating in the defense of a thesis. The goal of the M.S. degree program is to prepare the students with the necessary skills to conduct research in the field of Earth System Science and Policy. This degree is designed to help the students develop a career in fields that require research capabilities. In conjunction with the six overall learning outcomes for the department, the M.S. students are able to:

1. Initiate scientific inquiry through critical evaluation of existing knowledge.

2. Synthesize and communicate the results of analysis in a coherent and well-structured report.

Doctor of Philosophy – Ph.D.

The Ph.D. degree is an advanced research oriented program which involves conducting original research culminating in the defense of a dissertation and in peer reviewed publications. The goal of the Ph.D. degree program is to prepare students for a career in innovative research and/or academia. This degree is designed to train students to become high level researchers who will generate new knowledge in the field of Earth System Science and Policy, and sustainability. In conjunction with the six overall learning outcomes for the department, the Ph.D. students are able to:

1. Critically evaluate and identify gaps in existing knowledge.

2. Generate rigorous scientific inquiry that is original and bridges the identified gap in scientific knowledge.

3. Synthesize and communicate the results of research in the form of a dissertation, peer reviewed publication(s), and professional presentations.

III. ESSP UNDERGRADUATE DEGREE

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Undergraduate Minor in Sustainability Studies

The ESSP Minor in Sustainability Studies is to help future leaders of society acquire knowledge and develop skills in building a sustainable stewardship of our planet, by seeking balance between the three sustainability pillars (environment, society, economy). The integrated curriculum of the Minor will promote critical thinking and problem solving through a combination of classroom learning and studies of research and management of Earth system resources.

The core objectives for the ESSP Minor in Sustainability Studies are:

1. To help students acquire interdisciplinary knowledge and understanding of theories and practices of sustainability;

2. To engage students in active learning opportunities which develop skills in writing and critical analysis, and an appreciation for valuing diversity both in culture and the environment;

3. To apply a holistic/systems approach to problem solving within the coupled human-natural system; and

4. To prepare students to be life-long learners and competitive professionals in a variety of careers.

Upon completion of the program students will have acquired

1) the fundamentals of sustainability and sustainability science; 2) a multidisciplinary approach to problem solving for sustainability and

sustainability-related issues; 3) a set of skills and tools pertinent to solve problem within the coupled human-

environment.

IV. ASSESSMENT OF GOALS (GRADUATE) This Assessment of Goals was redefined during the ESSP retreat in August 2013 to fit the new Departmental goals and Student Learning Outcomes. This new criteria will start being implemented during the academic year 2014. However, to keep consistency between yearly assessments, the 2013 annual report will try, as much as possible, to follow that new matrix. How a goal is assessed:

1. Three levels of ability: acquired, needs improvement, not acquired 2. Analysis of the results

a. Are we doing good, and why it is if not. 3. Closing the loop

a. Taking action according to the analysis of the results

The main criteria for the six departmental goals are as followed:

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Goal 1 (Earth System Science)

1. Assignments

a. Class assignments

b. Lab assignments

2. Capstone project

3. Final exams

4. Thesis/Dissertation/Final Report (M.E.M.)

a. Discussion

Goals 2 and 6 (technology)

1. Assignments


b. Lab assignments

2. Identify technology needed to carry out research

a. Go beyond what is discussed in the class

3. Final analysis projects

a. Block presentations

b. Thesis/dissertation

Goal 3 (Policy and human-environment relationships)

1. Assignments


b. Lab assignments

2. Capstone project

3. Final exam


a. Discussion

Goal 4 (communication):

Oral presentations

1. Content

a. How it is organized and how it is explained

i. Knowledge of material

ii. Explanation of figures, graphs, tables, etc.

iii. Consistency of content (e.g. units)

iv. Balance (amount) of text, figures, graphs, etc.

v. references

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2. Delivery

a. Dress

b. Volume

c. Time

d. Speaking to audience

e. Not simply reading slides

3. Interaction

a. Listening to questions and providing answers related to question

Written papers

1. Content





2. Readability

a. Spelling

b. Sentence structure

c. Paper structure

3. Presentation

a. Formatting

b. Quality of graphs, figures, tables, etc.

4. References

a. Citation within text

b. Proper citation in reference section

c. Acknowledgements

Goal 5 (multi-disciplinary teams)

1. Group projects and group assignments

a. group presentations

b. balance of material

c. peer evaluation

d. exit and alumni survey

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DEPARTMENTAL PLAN FOR ASSESSMENT OF STUDENT LEARNING

EARTH SYSTEM SCIENCE AND POLICY

***REVISED – AUGUST 2013***

These update of the Departmental Plan for Assessment of Student Learning is to refine and specify the mission, goals, and student learning outcomes for the Department as a whole, and for each specific degree, M.E.M., M.S., and Ph.D. The update goal is to:

1. Define the mission of the ESSP Department, the Departmental goals and Departmental student learning outcomes.

2. Define the date on the mission, and goals of the ESSP Department and the three Graduate degree

I. ESSP DEPARTMENT

ESSP Mission Statement To provide an integrated and creative learning environment that fosters intellectual growth, critical thinking, and practical engagement in research and sustainable management of the Earth system and resources. Departmental Goals To fulfill the mission, the overall goal is to promote sustainability by pursuing:

1. Excellence in learning through a student-structured curriculum, a multi-disciplinary teaching approach, and experiential learning environments.

2. Excellence in discovery through research driven by societal needs and values

and occurs within an Earth System Science paradigm.

3. Excellence in engagement through outreach, service, and practical experience, which put knowledge related to Earth System Science and Policy to work.

The overall Student learning outcomes for all graduate degree programs are:

1. A breadth of knowledge in Earth System Science and Policy and the ability to apply that knowledge to address societal-driven sustainability science research, with a broad sense of ethical and professional responsibilities.

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2. A strong knowledge of multi-scale processes, cutting-edge computer technology, geographical information systems (GIS), remote sensing, and quantitative analysis.

3. A strong knowledge of environmental policy, and environmental and resource economics related to human-environment interactions.

4. Written and oral communication skills that will facilitate the transfer of knowledge to support actionable decisions.

5. The ability to function within multi-disciplinary teams to accomplish common goals.

6. An awareness of and preparation for a lifetime of learning.

II. ESSP MASTER DEGREES

Master of Environmental Management – M.E.M. The M.E.M. degree is a professional program which emphasizes practical experience especially through an internship. The goal of the M.E.M. degree program is to help the students develop the capabilities for a career in environmental management, sustainable development, or environmental policy. In conjunction with the six overall learning outcomes for the department, the M.E.M. students are able to:

1. Implement their knowledge into practical applications especially through a successful internship experience.

2. Holistically apply particular learned skill sets and acquire additional skills needed for development of a desired professional career path.

Master of Science – M.S.

The M.S. degree is a research oriented program which involves conducting a research project culminating in the defense of a thesis. The goal of the M.S. degree program is to prepare the students with the necessary skills to conduct research in the field of Earth System Science and Policy. This degree is designed to help the students develop a career in fields that require research capabilities. In conjunction with the six overall learning outcomes for the department, the M.S. students are able to:

1. Initiate scientific inquiry through critical evaluation of existing knowledge.

2. Synthesize and communicate the results of analysis in a coherent and well-structured report.

Doctor of Philosophy – Ph.D. The Ph.D. degree is an advanced research oriented program which involves conducting original research culminating in the defense of a dissertation and in peer reviewed publications. The goal of the Ph.D. degree program is to prepare students for a career

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in innovative research and/or academia. This degree is designed to train students to become high level researchers who will generate new knowledge in the field of Earth System Science and Policy, and sustainability. In conjunction with the six overall learning outcomes for the department, the Ph.D. students are able to:

1. Critically evaluate and identify gaps in existing knowledge.

2. Generate rigorous scientific inquiry that is original and bridges the identified gap in scientific knowledge.

3. Synthesize and communicate the results of research in the form of a dissertation, peer reviewed publication(s), and professional presentations.

III. ASSESSMENT OF GOALS

This Assessment of Goals was redefined during the ESSP retreat in August 2013 to fit the new Departmental goals and Student Learning Outcomes. This new criteria will start being implemented during the academic year 2014. However, to keep consistency between yearly assessments, the 2013 annual report will try, as much as possible, to follow that new matrix. How a goal is assessed:

1. Three levels of ability: acquired, needs improvement, not acquired 2. Analysis of the results

a. Are we doing good, and why it is if not. 3. Closing the loop

a. Taking action according to the analysis of the results

The main criteria for the six departmental goals are as followed:

Goal 1 (Earth System Science) 1. Assignments


b. Lab assignments

2. Capstone project

3. Final exams


a. Discussion

Goals 2 and 6 (technology) 1. Assignments


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b. Lab assignments

2. Identify technology needed to carry out research

a. Go beyond what is discussed in the class

3. Final analysis projects

a. Block presentations

b. Thesis/dissertation

Goal 3 (Policy and human-environment relationships) 1. Assignments


b. Lab assignments

2. Capstone project

3. Final exam


a. Discussion

Goal 4 (communication): Oral presentations

1. Content





iv. Balance (amount) of text, figures, graphs, etc.

v. references

2. Delivery a. Dress

b. Volume

c. Time

d. Speaking to audience

e. Not simply reading slides

3. Interaction

a. Listening to questions and providing answers related to question

Written papers

1. Content



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2. Readability

a. Spelling

b. Sentence structure

c. Paper structure

3. Presentation

a. Formatting

b. Quality of graphs, figures, tables, etc.

4. References

a. Citation within text

b. Proper citation in reference section

c. Acknowledgements

Goal 5 (multi-disciplinary teams) 1. Group projects and group assignments

a. group presentations

b. balance of material

c. peer evaluation

d. exit and alumni survey

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DEPARTMENTAL PLAN FOR ASSESSMENT OF STUDENT LEARNING

2007-2008 ACADEMIC YEAR

***REVISED*** December 2007

Department: EARTH SYSTEM SCIENCE AND POLICY 1. Mission Background – The 20th century was extraordinary in that a single species became the dominant force in modifying the global environment1. Humans have transformed between one-third and one-half of the Earth’s land surface; changed the chemical composition of the atmosphere (each breath today has 30% more carbon dioxide than before the Industrial Revolution); fix as much atmospheric nitrogen as do all natural causes combined; overexploit at least a fifth of the world’s marine fisheries; use more than half of all available freshwater; and have facilitated a mass extinction event that is 100-1000 times the background rate2. It is now clear that humanity is changing the world faster than it can understand the consequences. A new way of thinking about the world has become increasingly common in order to solve the complex resource and environmental problems that we collectively face. Although substantial progress has been made towards understanding, protecting, and restoring our common environment, immense challenges still lie ahead. In order to better predict the consequences of our actions, it has become necessary to treat the Earth as a system of integrated components that are interdependent, rather than the sum of discrete parts that act independently. Consequently, a new kind of education has arisen to prepare citizenry to accept responsibility for management of the planet. What is Earth System Science and Policy? – The Earth System Science and Policy (ESSP) graduate program is intellectually centered on the science and policy of environmental sustainability. Sustainability science focuses on the dynamic interactions between nature and

1 McNeill, J. R. 2000. Something New Under the Sun: An Environmental History of the Twentieth-Century World. W.W. Norton & Co., New York. 2 Vitousek, P. M. et al. 1997. Human domination of Earth’s ecosystems. Science, 275: 494.

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society by meeting human needs and values while preserving the planet’s life support systems3,4. The central goal of environmental sustainability is to live off nature’s interest rather than off its capital, thereby keeping intact the vital ecosystem services that nature provides. Sustainability science is, consequently, committed to a problem-driven agenda and is not confined to exclusively ‘applied’ research. In fact, pursuing solutions to practical, real-world sustainability problems is driving the science to address an array of fundamental questions. For example, what determines the vulnerability or resilience of the nature-society systems in particular kinds of places and for particular types of ecosystems and human livelihoods?5 Sustainability science is an intellectually exciting, growing discipline that bridges scholarship and practice, global and local perspectives, and scientific and social disciplines to address a common theme: meeting the needs of society while sustaining the life support systems of the planet by building an understanding of the relationship between nature and society. The graduate program in Earth System Science and Policy is organized around the field of environmental sustainability and offers three degrees: Master of Environmental Management, Master of Science, and Doctor of Philosophy. This relatively new program grew out of a recognized need for comprehensive research and educational programs that provide practical engagement in research and management of the Earth system and resources. An editorial from the American Association for the Advancement of Science concluded that “it is hard to imagine a more important discipline than Earth System Science.”6 A presidential address to the AAAS linked the human prospect to “new ways of thinking-an integrated multidimensional approach to the problems of global sustainability.”7 In a 1993 report of the National Research Council on Solid-Earth Sciences and Society, a major conclusion was “this [Earth System Science] process-orientated, integrated, global approach should be incorporated into revised earth science curricula in universities and schools.” A 1998 report of the Earth System Sciences Committee of the NASA Advisory Council recommended that NASA undertake a comprehensive research program and called for a major new synthesis and understanding of the Earth system.” Many of the committee’s recommendations were implemented and NASA created the Earth System Enterprise program. In addressing public concerns about environmental issues, including air and water pollution, nuclear waste disposal, the ozone hole, invasive plants and animals, biodiversity, and global climate change, the scientific community has realized how interrelated the components of the Earth’s systems are. While the critical parts – processes in the biosphere, hydrosphere, atmosphere, and lithosphere – are studied in detail within the boundaries of traditional disciplines, how the parts combine and interact is the key to understanding how our planet works, its past history, and its likely future. The idea of “Earth System Science” has emerged, not as a loosely anchored “interdisciplinary” subject, but as the driving concept for major international scientific and policy efforts. Scientists also now recognize that economic and public policies, initiated either by individuals or their governments, have environmental 3 Kates, R. W. et al. 2001. Sustainability science. Science, 292: 641-642. 4 Clark, W. C., and N. M. Dickson. 2003. Sustainability science: The emerging research program. Proceedings of the National Academy of Sciences USA, 100: 8059-8061. 5 Turner, et al. 2003. A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences USA, 100: 8074-8079. 6 Lawton, J. 2001. Editorial: Earth system science. Science, 292: 1965. 7 Raven, P. H. 2002. Science, sustainability, and the human prospect. Science, 297: 954-958.

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consequences; and that, conversely, environmental parameters inescapably bound economic and political policies.

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2. Program Objectives The Earth System Science and Policy graduate program was organized in response to the developing integrated, interdisciplinary approach to understanding and managing the Earth and is at the intersection between science and human needs and values. The educational focus of the program is thematic, emphasizing practical experience, student-centered learning, integration of knowledge across traditional disciplinary boundaries, and active dialogue both in and outside the classroom.

Mission Statement. – to provide an integrated and creative learning environment that fosters intellectual growth, critical thinking, and practical engagement in research and management of the Earth system and resources.

The ESSP program encourages students from diverse backgrounds and perspectives to work collectively on relevant problems with the common goal of serving humankind’s needs for an environmentally sustainable and prosperous future. To achieve the ESSP program’s mission, we apply strategies that target specific goals in the area of sustainability science and Earth System Science and Policy. The strategies are linked by a set of overarching organizing principles that are essential to all program activities.

Excellence in learning. In order to represent the full complexity of nature and sustainability science, crucial elements of program’s learning objectives include: a student-structured curriculum, a multi-disciplinary teaching approach, and experiential learning environments.

Excellence in discovery. Research within the program is driven by societal

needs and values and occurs within an Earth System Science paradigm, in which the Earth is treated as a single system that cannot be understood by summing the features of its component parts.

Excellence in engagement. Through its outreach and service activities, one of

the chief aims of the program is to put knowledge to work creating new opportunities that advance society, solve scientific and social problems related to Earth System Science, and empower citizens to make informed decisions about their environment.

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Given the broad mission statement and the overarching organizing principles of the ESSP program, specific program goals specify learning outcomes for graduates of the program. These program goals specify outcomes for the entire ESSP curriculum.

Earth System Science and Policy Program Goals

1. Students will possess a breadth of knowledge in Earth System Science and Policy and will be able to apply that knowledge to address societal-driven, sustainability science research.

2. Students will have a strong foundation in basic science,

applications-driven science, geographical information systems (GIS), remote sensing, environmental policy, and statistics.

3. Students will gain valuable hands-on experiences and will

be able to conduct experimental work needed to substantiate theoretical developments.

4. Students will possess written and oral communication skills

that will help them present their ideas effectively to their peers and the public.

5. Students will be able to function within multidisciplinary

teams to accomplish goals of interest to the group. 6. Students will have skills and experience using cutting-edge

computer technology to solve complex research and applications problems.

7. Students will be aware of issues of scale associated with

environmental sustainability and Earth System Science and Policy (i.e. spatial, temporal, impact, etc.), and have a broad sense of their ethical and professional responsibilities.

8. Students will be aware and prepared for a lifetime of

learning.

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3. Assessment Methods The Earth System Science and Policy graduate program utilizes nine primary assessment methods to evaluate learning outcomes for each of the program goals. These include:

a. Completion of whole fundamental courses, i.e. ESSP 501, ESSP 502. These two suites of ESSP courses total 20 credit hours for each ESSP student. Together they provide an overview of the fundamental issues associated with Earth System Science and Policy. Material is generally presented in a “situational” in a problem-based learning environment. Special emphasis is given to written reports and team-based projects, which foster communication and cooperation within a positive multi-disciplinary work environment.

b. Course evaluations. Every ESSP course and all learning blocks within the ESSP

501/502 suites of classes include standardized course evaluations. These evaluations are a means to produce useful feedback which the instructor can use to improve their quality of instruction. These evaluations help in the process of gathering information about the impact of learning and of teaching practice on student learning, analyzing and interpreting this information, and responding to and acting on the results.

c. Assignment to and progress towards completion of a faculty-advised research

project. Every ESSP student is assigned to work directly with a faculty advisor on a research project as part of their GRA responsibilities. These projects often include the student’s thesis project, but may also include responsibilities significantly beyond their research project.

d. Regular reviews of student progress by student’s graduate advisory committee and

the UND Graduate School, i.e. comprehensive exam, research proposal, thesis defense, etc. Every ESSP student is required to establish a graduate advisor committee that oversees, evaluates, and provides guidance towards the successful completion of the student’s program of study. The UND Graduate School outlines deadlines for each benchmark that each student must achieve. Additionally, the advisory committee and Dean of the Graduate School evaluate these benchmarks for overall scholarly quality.

e. Participation in scholarly conferences. As part of the ESSP program, each student is

expected to participate in at least one scholarly conference during their program of study. These conferences are typically ones where the student presents the results of their research project and include the UND Scholarly Activity Forum and various other professional conferences.

f. Participation in the department’s brown bag luncheon seminar series. Each ESSP

student is encouraged and expected to give at least one brownbag luncheon seminar presentation during their program of study. These presentations can be on any scholarly subject of their choice, but typically involve preliminary results of their thesis projects.

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g. Student annual evaluations from the department. All ESSP students receive an annual evaluation that is composed of three data sources. These include: 1) statement from each student, 2) completed evaluation matrix from each student’s GRA supervisor, and 3) completed evaluation matrix from each student’s major professor. All data sources are compiled and summarized into a review letter that is given to the student. The review rubric includes numerous evaluation areas, including a) quantity of work, b) quality of work, c) teamwork, d) initiative/resourcefulness, e) leadership, f) dependability, g) attendance, h) communication skills, i) knowledge of specific area of study, and j) overall knowledge of Earth System Science/Policy.

h. Group data from students. All ESSP students are invited to and encouraged to attend

regular programmatic focus groups, typically involving a free lunch for the students. These focus groups generally occur every six weeks or so, and involve at least one ESSP faculty member. Typically, three fundamental questions are asked: 1) What aspects of the program do you like the most and why? 2) What aspects of the program would you like to see improved or discontinued? 3) How prepared do you feel to move on to the next phase of your career?

i. Exit interview data for graduates and students leaving the program. All students

graduating from or otherwise leaving the program give an exit interview to the chair. Each interview typically involves at least three questions. These include: 1) What did you like the most about the ESSP program and why? 2) What did you like the least? 3) What would you change about the program that would have made your learning experience better?

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Table 1. Relationship of program goals of the Earth System Science and Policy Graduate Program to the primary assessment methods Earth System Science and Policy Program Goals. Upon graduation with a major in ESSP, students should be able to demonstrate that they can…

Primary Assessment Tools

1. Display a breadth of knowledge in Earth System

Science and Policy and apply that knowledge to address societal-driven sustainability science research

• Completion of whole fundamental courses, i.e. ESSP 501 and 502

• Course evaluations • Progress towards and/or completion of faculty-

assigned research project • Regular reviews of progress by student’s advisory

committee and UND Graduate School • Participation in scholarly conferences • Participation department’s brownbag seminar series • Student annual evaluations • Group data from students • Exit interviews

2. Display a strong foundation in basic science,

applications-driven science, geographical information systems (GIS), remote sensing, environmental policy, and statistics




committee and UND Graduate School • Participation in scholarly conferences • Participation department’s brownbag seminar series • Student annual evaluations • Group data from students • Exit interviews

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Table 1 continued. Relationship of program goals of the Earth System Science and Policy Graduate Program to the primary assessment methods Earth System Science and Policy Program Goals. Upon graduation with a major in ESSP, students should be able to demonstrate that they can…


3. Use hands-on experiences in order to conduct

experimental work needed to substantiate theoretical developments

• Completion of whole fundamental courses, i.e.

ESSP 501 and 502 • Progress towards and/or completion of faculty-


committee and UND Graduate School • Participation department’s brownbag seminar series • Student annual evaluations • Group data from students • Exit interviews

4. Display written and oral communication skills

that will help them present their ideas effectively to their peers and the public


• Progress towards and/or completion of faculty-assigned research project

• Regular reviews of progress by student’s advisory committee and UND Graduate School

• Participation in scholarly conferences • Participation in the department’s brown-bag

seminar series • Student annual evaluations •

5. Function within multidisciplinary teams to

accomplish goals of interest to the group • Completion of whole fundamental courses, i.e.

ESSP 501 and 502 • Participation in scholarly conferences • Participation department’s brownbag seminar series • Course evaluations • Progress towards and/or completion of faculty-

assigned research project • Student annual evaluations

6. Use skills and experience with cutting-edge

computer technology to solve complex research and applications problems


• Participation in scholarly conferences • Participation department’s brownbag seminar series • Course evaluations • Progress towards and/or completion of faculty-

assigned research project • Student annual evaluations

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Table 1 continued. Relationship of program goals of the Earth System Science and Policy Graduate Program to the primary assessment methods Earth System Science and Policy Program Goals. Upon graduation with a major in ESSP, students should be able to demonstrate that they can…


7. Display awareness of issues of scale associated

with environmental sustainability and Earth System Science and Policy (i.e. spatial, temporal, impact, etc.), and have a broad sense of their ethical and professional responsibilities



assigned research project • Participation in scholarly conferences • Participation department’s brownbag seminar series • Student annual evaluations • Group data from students

8. Display and awareness and are prepared for a

lifetime of learning

• Course evaluations • Participation in scholarly conferences • Group data from students • Exit interviews •

In addition to the above primary assessment tools, learning outcomes are also evaluated within the context of ESSP classes, especially the ESSP 501 and 502 courses (Table 2). These courses are extraordinary in that they comprise 20 total credit hours of graduate coursework for each student. Each course is divided into three subject-related blocks that provide the students with the opportunity to learn about, experience, and practically deal with numerous sustainability-based research and policy problems. Individual faculty members who teach ESSP courses regularly evaluate course products and assignments with our program goals in mind. Regular faculty meetings, an annual faculty and staff retreat, and regular communication among faculty allow course instructors to share their assignments and discuss how they relate to the above program goals.

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Table 2. Sample individual class assessment tools correlated with program objectives. Earth System Science and Policy Program Goals Sample Class Assessment Tools

Course # - Assignment Title/Description

1. a breadth of knowledge in Earth System Science

and Policy and will be able to apply that knowledge to address societal-driven sustainability science research

501 The Effect of Climate Change on

Biodiversity of North America block capstone project (Appendix 1)

501R Consumer Product Life Cycle Analysis 501L Alternative Fuels Fact Sheet 502 Mapping Nitrogen (N) Credit for the Red

River Valley 502R Economic Valuation of Water Resources 502L CO2 in the Atmosphere – A Historical Look

Biogeochemistry Lab (Appendix 2) 520 Evaluation of Models Estimating

Evapotranspiration 570 Sustainability Communications Capstone

Project (Appendix 3) 594 Predictive Distributional Modeling of

Vector-Borne Malaria Independent Study 597 Semester Internship within the professional

environment 998 Earth Science-Based Thesis Project

2. a strong foundation in basic science, applications-

driven science, geographical information systems (GIS), remote sensing, environmental policy, and statistics

501 Research on the Mind lecture, discussion,

and lab assignment (Appendix 4) 501R Energy & Economy Lecture & Discussion 501L Introduction to GIS;

Spatial Analysis of Ecosystem Productivity 502 GIS Definitions of Landscapes 502R GIS Applications Discussion 502L Global Temperature Change

Biogeochemistry Lab (Appendix 5) 520 Statistics Theory in Earth Modeling 570 Environmental Advertisement Analysis

(Appendix 6) 594 Research Literature Review 597 Semester Internship within the professional


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Table 2 continued. Sample individual class assessment tools correlated with program objectives. Earth System Science and Policy Program Goals Sample Class Assessment Tools


3. valuable hands-on experiences and will be able to

conduct experimental work needed to substantiate theoretical developments

501 Dutch Elm Disease in Grand Forks 501R Energy Block Press Review 501L Species Predictive Distributional Modeling

(Appendix 7) 502 Micro-Economics of Bottled Water

(Appendix 8) 502R Full Cost Accounting Analysis of a

Hypothetical Landfill (Appendix 9) 502L Remote Sensing/GIS Lab 520 Earth Modeling Literature Review 540 Remote Sensing in the Developing World 570 Analysis of Communications Models Used

in Environmental Messages 594 Predictive Distributional Modeling of

Vector-Borne Malaria 597 Semester Internship within the professional


4. written and oral communication skills that will help

students present their ideas effectively to their peers and the public

501 Biological Diversity Policy Debate

(Appendix 10) 501R Policy Brief Workshop 501L Biosphere Block Capstone Presentation 502 Mapping Nitrogen (N) Credit for the Red

River Valley Formal Presentation 502R Land Use/Land Cover Discussion 502L Full Cost Accounting Assignment

Involving Solid Waste Management and the Issue of Landfilling Waste (Appendix 11)

520 Earth Modeling Review Paper 540 Remote Sensing Technologies Presentation 570 Course Capstone Communications Paper &

Presentation (Appendix 12) 594 Professional Presentation: Predictive

Distributional Modeling of Vector-Borne Malaria

597 Semester Internship within the professional environment

998 Written Thesis & Oral Defense

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5. function within multidisciplinary teams to

accomplish goals of interest to the group

501 Sustainability Academic Controversy 501R Biosphere Block Capstone Projects

(Appendix 13) 501L Group work within labs 502 Landfill: Waste Materials & Decision

Making 502R Full Cost Accounting Analysis of a

Hypothetical Landfill 502L Hydrology of Devils Lake 520 Earth Model Development Project 540 Remote Sensing Reading Group 570 Environmental Ethics and Philosophy

Review & Discussion 597 Semester Internship within the Professional

Environment 998 Thesis data collection & analysis

6. skills and experience using cutting-edge computer

technology to solve complex research and applications problems

501 Biogeography: Predictive Distributional

Modeling 501R Energy Block Capstone Project poster

preparation 501L Introduction to GIS – Biosphere Block Lab

(Appendix 14) 502 GIS Definition of Landscape 502R North Dakota Waffle Project 502L Advanced GIS Applications Lab

(Appendix 15) 520 Statistics of Modeling 540 ERDAS IMAGINE/ArcMap Lab 570 Communications Analysis Poster

Presentation (Appendix 16) 594 Predictive Distributional Modeling

Algorithm Use 597 Semester Internship within the Professional

Environment 998 Thesis data analysis

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7. awareness of issues of scale associated with

environmental sustainability and Earth System Science and Policy (i.e. spatial, temporal, impact, etc.), and have a broad sense of their ethical and professional responsibilities

501 Nature-Based Tourism in the Pembina

Gorge, North Dakota (Appendix 17) 501R Steam Generation Plant Field Trip &

Discussion 501L Biodiversity-Societal Impacts & Policy

Implications 502 Media advisory: Climate experts can

comment on 'The Day After Tomorrow' – A Science Review (Appendix 18)

502R Hydrology of Devils Lake Ethics Discussion

502L Advanced GIS Measurement Lab (Appendix 19)

520 Validation of a Modeling Result Using Remote Sensing Data

540 Fundamentals of Remote Sensing 570 Sustainability Ethics Lecture & Discussion 594 Ethical Implications of Arboviral Disease

Distributional Modeling 597 Semester Internship within the Professional

Environment 998 Earth Science-Based Thesis Project

8. awareness and preparedness for a lifetime of

learning

501 Sustainability Book Club & Discussion

Group 501R Scientific Journal Student-Led Discussion

(Appendix 20) 501L The Rudiments of Research Biosphere Lab 502 Building Bridges – The Purpose of Earth

System Science – An Example From the Hydrologic Cycle (Appendix 21)

502R Media advisory: Climate experts can comment on 'The Day After Tomorrow' – A Science Review

502L Movement of Crop Material From One Year to Another (Appendix 22)

520 Earth Modeling Complexity Discussion 540 Remote Sensing in the Developing World 570 Letter to the Editor assignment (Appendix

23) 594 Practical Application of Disease

Distributional Modeling 597 Semester Internship within the professional


15

Program learning outcomes are also evaluated within a myriad of other non-class program activities, including program-wide student presentations, participation in professional conferences, interactions with local stakeholders and user-groups, published professional papers, internships obtained and completed, placement within Ph.D. programs, and obtainment of jobs after graduation.

16

4. Timeline for Review of Program Assessment Results and Feedback to Curriculum

Results from the primary assessment tools are evaluated by ESSP faculty members throughout the academic year depending on the tool being utilized (Table 3). Table 3. Timeline for evaluation of results from assessment tools. Primary Assessment Tools Evaluation Timeframe Primary Evaluator 1. Completion of whole fundamental

courses, i.e. ESSP 501 and 502 December (for Fall semester) May (for Spring semester)

Block instructor Overall course instructor Department Chair (Hanley)

2. Course evaluations Informal evaluations throughout

academic year; formal evaluations given at the end of each block and reviewed upon return by UND

Block/course instructor Department Chair (Hanley)

3. Assignment to and progress

towards completion of a faculty-advised research project

Throughout year; faculty supervisors meet regularly with student workers

Faculty GRA supervisor Department Chair (Hanley)

4. Regular reviews of student

progress by student’s graduate advisory committee and the UND Graduate School, i.e. comprehensive exam, research proposal, thesis defense, etc.

Throughout year; deadlines for major activities established by department and UND Graduate School

Major professor Committee members (≥3 for M.S. and M.E.M. students; ≥5 for Ph.D. students) Dean of the Graduate School (Benoit)

5. Participation in scholarly

conferences

Throughout year

Major professor Faculty GRA supervisor Department Chair (Hanley)

6. Participation in the department’s

brown bag luncheon seminar series

Throughout year

Faculty organizers of brownbag seminar series (Kirilenko, Laguette)

7. Student annual evaluations from

the department

Feedback forms due in December; evaluations take place in January

Evaluation committee led by the Department Chair (3 faculty members total)

8. Exit interview data for graduates

and students leaving the program

December, May, August

Department Chair (Hanley)

17

Observations generated by all assessment methods contribute to regular and on-going curriculum and course development within the department. Additionally, in late summer (usually late July or early August) of each year, the faculty meet for a curriculum retreat in which all results from assessment activities are reviewed and curricular changes are considered. This curriculum retreat is directed by the Chair of the program and all faculty members are required to attend. During this retreat, six primary goals are achieved. These include:

1. Programs goals are reviewed 2. Assessment methods are reviewed 3. Assessment results are reviewed 4. Course objectives are reviewed 5. Block objectives are reviewed 6. Curricular changes are proposed

Finally, the overall ESSP curriculum is reviewed and student strengths and weaknesses are evaluated as they progress through the program. Explicit discussion identifies which goals are not being met adequately and how we as a faculty can address any weaknesses. Other Assessment Activities During the past year, the ESSP program underwent a New Program Review conducted by the UND Graduate School. The full review can be found on file in the Graduate School. One passage from the Conclusions and Recommendations section of this review is as follows:

“From information received from the ESSP program’s Annual Report, from data taken from the Graduate School data base, and from an interview with the Program’s Director, it appears that in the three years the ESSP program has been in existence it has been successful in meeting its program’s mission and goals. The program has a productive faculty in acquiring extramural funding to support the program and in publishing and presenting the results of their research. The program has been successful in recruiting and graduating students in an acceptable amount of time, with the students being successfully employed upon graduation. And the program’s faculty has been successful in providing service to the academic community and to the local and regional communities.”

A Full Program Review by the Graduate School is scheduled for 2012.

18

5.0 Results from Data Collection

ASSESSMENT TOOL #1:

COMPLETION OF WHOLE FUNDAMENTAL COURSES, I.E. ESSP 501, ESSP 502 These two suites of ESSP courses total 20 credit hours for each ESSP student. Together they provide an overview of the fundamental issues associated with Earth System Science and Policy. Material is generally presented in a “situational” in a problem-based learning environment. Special emphasis is given to written reports and team-based projects, which foster communication and cooperation within a positive multi-disciplinary work environment. Description of Core Courses Courses Name Description ESSP 501 Earth System Science and

Policy I An overview of the fundamental issues from five research areas: biodiversity and ecosystem functioning, climate and environmental change, land and resource management, environmental policy, management and communication, and human health and the environment. ESSP faculty and guest lecturers present background information relevant to the topics. Students are expected to engage actively in the learning process by determining what further information they need to understand the problem, researching the questions, and clearly and concisely present the findings of their research to one another.

ESSP 501R Earth System Science and

Policy Recitation Small group discussions to include many parties to an environmental issue

ESSP 501L Earth System Science and

Policy Laboratory Laboratory session.

ESSP 502 Earth System Science and

Policy II Course follows the design of ESSP 501 but with more emphasis on written reports and team projects. At the beginning of the semester, students will either select or be assigned a topic for an interdisciplinary team project for completion by the end of the semester. The team project helps students acquire an interdisciplinary outlook, and fosters communication and cooperation within a positive multi-disciplinary work environment. This will provide students with skills that are integral to the management of complex environmental problems they will face in the world beyond academia.

ESSP 502R Earth System Science and

Policy Recitation II Small group discussion

ESSP 502L Earth System Science and

Policy Laboratory II Laboratory session.

ESSP 540 Advanced Topics in

Geospatial Techniques This course will allow students to stay abreast of technological developments in a rapidly evolving field. Course contents will vary according to where the advances have the most immediate impact. The goal is to provide students exposure and hands-on experience needed to apply technologies to significant Earth System problems. Among technologies to be discussed are sensors for satellites and aircraft, data acquisition and image processing tools, verification and validation techniques, precision navigation by Global Positioning Satellites, and advanced uses Geographic Information Systems.

ESSP 570 Communicating

Environmental Information The focus of the class is on communication of scientific information to non-science audiences. Students will probe the role of communication in the public perceptions of environmental issues, examine the effectiveness of different tools in raising environmental awareness, explore the barriers that hinder effective communication and subsequent motivation for action, and profile a variety of environmental outreach activities. Ways to convert polarization among differing parties into consensus by communicating accurate, timely information will be explored.

19

Courses Name Description ESSP 594 Directed Study Directed reading or investigations tailored to the needs of individual students for advanced

knowledge in specific areas. Typically requires weekly meetings with assigned faculty member. Usually culminates in a paper on the specific topical area.

ESSP 596 Doctoral Research Doctoral research. ESSP 597 Internship Practical experience for ESSP students in a professional environment. ESSP 599 Special Topics Topics of current interest. May be provided by program or visiting ESSP faculty. ESSP 998 Thesis Thesis. ESSP 999 Dissertation Dissertation.

Summary of Courses Completed Student Courses Completed

ESSP 501

ESSP 501R

ESSP 501L

ESSP 502

ESSP 502R

ESSP 502L

ESSP 540

ESSP 570

ESSP 594

ESSP 596

ESSP 597

ESSP 599

ESSP 998

ESSP 999

Adhikari, Hom

Akudibillah,

Gordon

Aloysius, Noel

Atkinson, Lorilie

Babcock, Kristen

Berhane, Tedros

Bornemann,

Branden

Ciofani,

Leigh

Eggleston,

Sarah

Fieber-Beyer,

Sherry

Foster, Inga

Gadgil, Mandar

Gaffrey, Ken

Janke, Tyler

20

Student Courses Completed ESSP

501 ESSP 501R

ESSP 501L

ESSP 502

ESSP 502R

ESSP 502L

ESSP 540

ESSP 570

ESSP 594

ESSP 596

ESSP 597

ESSP 599

ESSP 998

ESSP 999

Mattis, Kristine

Mossett, Kandi

Nepal, Sandhya

Olson, Tim

Pettit, Penny

Reedy, Vishnu

Riepl, Jessica

Sardesai, Pushkaraj

Schultz, Jeannie

Sharkuu,

Anarmaa

Smith, Elliott

Springsteen,

Anna

Williams, Chris

Zhao, Longbin

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SSP 501/502a means to pnstruction. Trning and ofd responding

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22

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1

1.5

2

2.5

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3.5

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ESSP Courses 2007 Spring All UND Graduate Courses 2007 Spring

00.51

1.52

2.53

3.54

4.55

ESSP Courses 2006 Fall All UND Graduate Courses 2006 Fall All UND Courses 2006 Fall

23

00.51

1.52

2.53

3.54

4.55

ESSP Courses 2006 Spring All UND Courses 2006 Spring

24

ASSESSMENT TOOL #3:

ASSIGNMENT TO AND PROGRESS TOWARDS COMPLETION OF A FACULTY-ADVISED RESEARCH PROJECT

Every ESSP student is assigned to work directly with a faculty advisor on a research project as part of their GRA responsibilities. These projects often include the student’s thesis project, but may also include responsibilities significantly beyond their research project. Summary of Student Participation in Faculty Assigned Project Student Advisor Project Description Progress Adikhari, Hom Jhoti Hill An ecosystem services

assessment for Grand Forks county

Hom is undertaking a literature review and compiling preliminary data for his thesis work. He is also completing an online ArcGIS course.

Still developing skills at the beginning of the project but has a good attitude.

Akudibillah, Gordon Kirilenko Comparative analysis of

the artificial intelligent methods for predictive modeling using presence/pseudo-absence data

Building necessary skills and reading relevant literature

In progress

Atkinson, Lorilie Romsdahl Review and revision of

an internet survey – An evaluation of the “Infomart” Tool for Ag-Business Decision-makers

The students reviewed the Infomart Precision Farming Internet tool to assist in revising the evaluation survey. This assignment gave the student an understanding of and experience with SurveyMonkety as a potential tool for her own future research.

Completed satisfactorily

25

Student Advisor Project Description Progress Atkinson, Lorilie Mattis, Kristine Schultz, Jeannie

Romsdahl North Dakota climate change planning – A survey of Government decision-makers

Students assisted in proof reading, pre-testing, developing an address database, and bulk-mailing of a survey and follow-up postcards (to 495 addresses). Students assisted in developing a database and are responsible for transcribing data from the returned questionnaires into the database.

Students are near completion in transcribing data, with good progress to date; all other activities have been satisfactorily completed

Atkinson, Lorilie Mattis, Kristine Schultz, Jeannie

Romsdahl Creation of Endnote Library Databases for Environmental Science and Policy References

Students learned the basic components of the Endnote reference software program. Students were responsible for entering a designated set of references into topical Endnote databases.


Babcock, Kristen Hanley Ground beetle diversity

of the Glacial Ridge National Wildlife Refuge

Survey the ground beetle diversity from four habitat types at the GRNWR


Berhane, Tedros Zhang NSERC Education Building a

bibliographic database for studies that use DC-8 data

On-going, not yet completed

Bornemann, Branden Hill Temporal and spectral

dynamics of diverse land cover type from the EOS Land Validation Core Site Network

Branden is downloading, reprojecting and compiling time series MODIS and MISR data for a selection of sites across the USA

Catching up after some delayed progress. Had some uncertainty in developing his thesis project which interfered with GRA work. But, has good and responsible attitude.

26

Student Advisor Project Description Progress Ciofani, Leigh Laguette Bibliography on

Switchgrass Scholarly literature search

Partially achieved

Hanley Modeling the

distributions of encroaching shrubs on North Dakota grasslands

Use machine-learning algorithms to model the potential spatial distributions of woody shrubs throughout the Northern great Plains


Foster, Inga Hanley GIS Environmental

Layers for the Glacial Ridge National Wildlife Refuge

Produce GIS layers for use in mapping of the GRNWR


Janke, Tyler Hanley Determining Species

Pools of aquatic vegetation in the Glacial Ridge National Wildlife Refuge

Use of combination of field sampling and literature searching to establish the species pools of aquatic vegetation in the GRNWR


Nepal, Sandyha Kirilenko Climate Change

Scenarios Building climate change scenarios for the areas of interest

In progress

Olson, Tim Hanley Climate Change

Impacts on Nordus beetles of South America

Use machine-learning algorithms to model the spatial impacts of climate change on the distributions of species of Nordus throughout South America


Riepl, Jessica Laguette ASD data – from

ASCII to excel format To transform ASD field spectroradiometer data on switchgrass, collected during summer field season, into excel format

Achieved satisfactorily

Laguette Biomass Energy – Classification Potential Land-Use

To identify, locate, list and download satellite images, actual land-use classification and agrometeorlogical data

In progress

Sardesai, Pushkaraj Laguette Comparison of Economic and Energy Viability of Energy Crops

Energy and economic valuation study of crops associated with bioenergy


27

Student Advisor Project Description Progress Sharkuu, Anarmaa Kirilenko Historical and future

land use change in Grand Forks county

Building necessary skills and compiling preliminary data

In progress

Smith, Elliott Laguette Cattail progression

mapping to help wetland restoration and management

To identify cattail stands, acquired and process spatial images over those stands, make contact with wetland managers

In progress

Williams, Chris Laguette Organization of scientific literature and papers

To classify and file scientific literature and papers

Partially achieved

Zhao, Longbin Zhang Atmospheric correction

algorithm for the UND AgCam

Unfinished due to leave of absence

28

ASSESSMENT TOOL #4:

REGULAR REVIEWS OF STUDENT PROGRESS BY STUDENT’S GRADUATE ADVISORY COMMITTEE AND THE UND GRADUATE SCHOOL, i.e. comprehensive

exam, research proposal, thesis defense, etc. All ESSP students are required to establish a graduate advisor committee that oversees, evaluates, and provides guidance towards the successful completion of the student’s program of study. The UND Graduate School also outlines deadlines for each benchmark that each student must achieve. Additionally, the advisory committee and Dean of the Graduate School evaluate these benchmarks for overall scholarly quality. Summary of Student Milestones Achieved Milestones Overseen by Graduate Committee and UND Graduate School Student

Selected Advisor

Selected Committee

Submitted Program of

Study

Submitted Research/ Internship Proposal

Advanced

to Candidacy

Completed Comprehensive Exams

Completed Thesis/Inte

rnship

Graduated Adhikari,

Hom

Akudibillah,

Gordon

Aloysius,

Noel

Atkinson,

Lorilie

Babcock,

Kristen

Berhane,

Tedros

Bornemann,

Branden

Ciofani,

Leigh

Dahlen,

Bjorn Withdrew from program

Eggleston,

Sarah

Fieber-Beyer,

Sherry

Foster,

Inga

Gadgil,

Mandar Currently on leave of absence

Gaffrey,

Ken Withdrew from program

29

Janke, Tyler

Mattis,

Kristine

Mossett,

Kandi

Nepal,

Sandhya

Olson,

Tim

Pettit,

Penny

Reedy,

Vishnu

Riepl,

Jessica

Sardesai,

Pushkaraj

Schultz,

Jeannie

Sharkuu,

Anarmaa

Smith,

Elliott

Springsteen,

Anna

Williams,

Chris Withdrew from program

Zhao,

Longbin Currently on leave of absence

30

ASSESSMENT TOOL #5:

PARTICIPATION IN SCHOLARLY CONFERENCES As part of the ESSP program, each student is expected to participate in at least one scholarly conference during their program of study. These conferences are typically ones where the student presents the results of their research project and include the UND Scholarly Activity Forum and various other professional conferences. Summary of Student Participation in Scholarly Conferences 2007 Babcock, K., and R. S. Hanley. Fire-colored beetles (Coleoptera: Pyrochroidae) of three

wetland types from the Glacial Ridge National Wildlife Refuge. University of North Dakota Scholarly Forum, February 2007.

Berthier, J; Marchis, F.; Descamps, P.; Assafin, M.; Bouley, S.; Colas, F.; Dubos, G.; Emery, J.

P.; De Cat, P.; Farrell, J. A.; Leroy, A.; Pauwels, T.; Pollock, J. T.; Reddy, V.; Sada, P. V.; Vingerhoets, P.; Vachier, F.; Vieira-Martins, R.; Wong, M. H.; Reichart, D. E.; Ivarsen, K. M.; Crain, J. A.; LaCluyze, A. P.; Nysewander, M. C. 2007. An Observing Campaign of the Mutual Events Within (617) Patroclus-Menoetius Binary Trojan System, American Astronomical Society, DPS meeting #39, #35.05.

Ciofani, L., and R. S. Hanley. Future climate change in the U.S. Upper Midwest: An analysis of

projected temperature and precipitation on a regional scale. Graduate Student Climate Conference, University of Washington Program on Climate Change, Seattle, Washington, October 20, 2007.

Ehrenfreund, P.; Foing, B. H.; Veillet, C.; Wooden, D.; Gurvits, L.; Cook, A. C.; Koschny, D.;

Biver, N.; Buckley, D.; Ortiz, J. L.; di Martino, M.; Dantowitz, R.; Cooke, B.; Reddy, V.; Wood, M.; Vennes, S.; Albert, L.; Sugita, S.; Kasuga, T.; Meech, K. 2007. SMART-1 Impact Ground-based Campaign, 38th Lunar and Planetary Science Conference, held March 12-16, 2007 in League City, Texas. LPI Contribution No. 1338, p.2446

Fieber-Beyer, S. K.; Gaffey, M. J.; Abell, P. A.; Reddy, V. 2007. Mineralogical

Characterization of Near Earth Amor Asteroid 1036 Ganymed, 38th Lunar and Planetary Science Conference, held March 12-16, 2007 in League City, Texas. LPI Contribution No. 1338, p.1695

Foster, I., and R. S. Hanley. Blue darner diversity: using Maxent to construct a species pool for

a northern tallgrass prairie at the Glacial Ridge National Wildlife Refuge. University of North Dakota Scholarly Forum, February 2007.

Hanley, R. S., Ciofani, L., T. Olson, and V. Reedy. Identification of the five most important

ecological questions of high policy relevance: International, national (United States) and

31

local (Grand Forks, ND) perspectives. University of North Dakota Scholarly Forum, February 2007.

Kelley, M. S.; Gaffey, M. J.; Reddy, V. 2007. Near-IR Spectroscopy and Possible Meteorite

Analogs for Asteroid (253) Mathilde, 38th Lunar and Planetary Science Conference, held March 12-16, 2007 in League City, Texas. LPI Contribution No. 1338, p.2366

Reddy, V; Gaffey, M. J.; Binzel, R. P.; Hardersen, P. S.; Kumar, S. 2007. Constraining

Composition of Potentially-Hazardous Asteroid 2006 WH1 via Near-IR Spectroscopy, American Astronomical Society, DPS meeting #39, #13.05.

Reddy, V.; Cloutis, E. A.; Craig, M. A.; Gaffey, M. J., (2007) Spectral Calibration of

Orthopyroxene-Clinopyroxene Mixtures: Implications for Interpreting Asteroid Spectra. Reddy, V.; Dyvig, R. R.; Pravec, P.; KuNirák, P.; Gajdo, E.; Galád, A.; Korno, L.; Ries, J. G.,

(2007) Photometric Observations of Binary Near-Earth Asteroid (7088) Ishtar and (11405) 1999 CV3, 38th Lunar and Planetary Science Conference, held March 12-16, 2007 in League City, Texas. LPI Contribution No. 1338, p.1239.

Reddy, V.; Gaffey, M. J.; Abell, P. A.; Hardersen, P. S., (2007) Mineralogical Investigation and

Thermal Modeling of Near-Earth Asteroids (11405) 1999 CV3, 2000 BD19, 2003 SA224, and 2005 YY93, 38th Lunar and Planetary Science Conference, held March 12-16, 2007 in League City, Texas. LPI Contribution No. 1338, p.1238.

Springsteen, A., and R. S. Hanley. From grasslands to woodland: A 42-year chronosequence of

woody plant expansion in Mandan, North Dakota. M.S. thesis preliminary results – total soil carbon aand nitrogen changes. University of North Dakota Scholarly Forum, February 2007.

2006 Abell, P.A., Vilas, F., Reddy, V., Gaffey, M.J., Jarvis, K.S. 2006. Visible and Near-Infrared

Spectroscopy of Potentially Hazardous Asteroid (68950) 2002 QF15. American Astronomical Society, DPS meeting #38.

Babcock, K., and R. S. Hanley. Fire-colored beetles (Coleoptera: Pyrochroidae) of the Glacial

Ridge National Wildlife Refuge, northwest Minnesota. Entomological Society of America National Meeting, Indianapolis, IN, December, 2006.

Foster, I., and R. S. Hanley. Saving lives or serving filth? Irradiation: An analysis of a

communication divide. University of North Dakota Graduate School Scholarly Activity Forum, February, 2006.

Foster, I., and R. S. Hanley. Odonata Diversity at the Glacial Ridge National Wildlife Refuge:

Combining Surveying Within a Northern Tallgrass Prairie and Predictive Distributional Modeling. Entomological Society of America National Meeting, Indianapolis, IN, December, 2006.

32

Janke, T., R. S. Hanley, W. D. Svedarsky, and R. Crawford. Evaluating the Re-Vegetation of

Restored Wetlands in NW Minnesota: A M.S. Thesis Progress Report. University of North Dakota Graduate School Scholarly Activities Forum, February, 2006.

Reddy, V., Gaffey, M.J., Abell, P.A., Hardersen, P.S. 2006. Compositional Investigation of

Near-Earth Asteroids 6456 Golombek, (5660) 1974 MA, (13553) 1992 JE, In Lunar and Planetary Science XXXVII, Abstract #1746, Lunar and Planetary Institute, Houston (CD-ROM).

Reddy, V., Gaffey, M.J., Hardersen, P.S., Abell, P.A., Kumar, S. 2006. Constraining Albedo

and Composition of Potentially-Hazardous Asteroids 2004 XP14 and (100085) 1992 UY4 via Near-IR Spectroscopy. American Astronomical Society, DPS meeting #38.

Reddy, V., Gaffey, M.J., Abell, P.A., Hardersen, P.S. 2006. Near-IR Reflectance Spectroscopy

of Near-Earth Asteroid (23183) 2000 OY21: Evidence for Ca-rich Clinopyroxene in the Surface Assemblage. Geological Society of America Meeting Abstract, Philadelphia.

2005 Eggleston, S., P. Pettit, K. Gaffrey, R. S. Hanley, and J. Tyndall. Insect Populations and the

Decline of Threatened Prairie Birds in North America: A Proposed Study from a Student Project in UND’s ESSP Program. University of North Dakota Graduate School Scholarly Activities Forum, February 2005.

Janke, T., N. Aloysius, R. S. Hanley, and J. Tyndall. Balancing Economic Growth with Habitat

Conservation: A Stewardship Plan for a Residential Development near a Forest Remnant in Grand Forks, North Dakota. University of North Dakota Graduate School Scholarly Activities Forum, February 2005.

2004 Dahlen, B. F., and R. S. Hanley. BugHunter: An instrument for unmanned airborne

entomological collection. Entomological Society of America National Meeting, November 2004.

Dahlen, B. F., and R. S. Hanley. Remote sensing applications in predictive distributional

modeling of vector-borne diseases. International Symposium on Geoinformation, Kuala Lumpor, Malaysia, September, 2004.

Hanley, R. S., and Dahlen, B. F. Predictive Distributional Modeling of Malaria in Borneo using

Remote Sensing and Primary Vector Mosquito Bionomics. Entomological Society of America National Meeting, November 2004.

33

ASSESSMENT TOOL #6:

PARTICIPATION IN THE DEPARTMENT’S BROWN BAG LUNCHEON SEMINAR SERIES

Each ESSP student is encouraged and expected to give at least one brownbag luncheon seminar presentation during their program of study. These presentations can be on any scholarly subject of their choice, but typically involve preliminary results of their thesis projects.

Summary of Results

Date Speaker Title

Spring 2007

February 16th, 2007 Vishnu Kanupuru, Ph.D. student

Tomb Raiders: Understanding history of science in 19th century Colonial world

February 23rd, 2007 Anna Springsteen M.S. student

From Grassland to Woodland: A 42-year chronosequence in Mandan, ND

March 2nd, 2007 Inga Foster M.S. student

Odonata diversity & the Glacial Ridge National Wildlife Refuge.

March 30th, 2007 Tedros Berhane M.S. student

Remote Sensing of Heat Flux

April 13th, 2007 Andrei Kirilenko ESSP faculty

Predicting climate change impact on insect biodiversity: comparison of scenarios

April 20th, 2007 Lijian Shi Visiting student

Use of Satellite Synthetic Aperture Radar Imagery to Map Oil Spills in the East China Sea

April 27th, 2007 Leigh Ciofani M.S. student

Woody Shrub Encroachment in North Dakota Grasslands: Using Predictive Modeling to Examine Key Players and Management Implications

Fall 2007

September 28th, 2007 Leigh Ciofani M.S. student

Predictive Distribution Modeling: An Introduction to the Details

October 5th, 2007 Sherry Fieber-Beyer Ph.D. student

Spinel-Bearing asteroids… the most ancient asteroids in the solar system.

October 12th, 2007 Tedros Berhane M.S. student

Remote Sensing of Heat Fluxes: Validation and Inter-sensor Comparison

October 19th, 2007 Rebecca Romsdahl Policy Questions Stemming from Climate

34

ESSP faculty Change Impacts on Isle Royal National Park

November 2nd,2007 Gordon Akudibillah M.S. student

The Effect of the Use of Resistant Cultivars on the Evolution of Tomato Leaf Curl Virus (TYLCV)

November 16th, 2007 Vishnu Kanupuru Ph.D. student

Made for Each Other?: Binary Asteroids in the Solar System

November 30th, 2007 Xiaodong Zhang ESSP faculty

Searching clouds in the ocean

Vishnu Kanupuru, Ph.D. student – Tomb Raiders: Understanding History of Science in 19th Century Colonial World (February 16, 2007)

This talk is a summary of work I did for the last four years reconstructing the life and works of British astronomer Norman Robert Pogson. Pogson is famous for devising the magnitude scale for stars which is one of the most fundamental elements of modern astrophysics. But he remained obscure till now due to his personality and the conflict he had with the British establishment. The work was done in collaboration with a Dr Keith Snedegar, member of International Astronomical Union History Panel. We basically reconstructed Pogson's life from archives in Oxford, Germany and field work in India and tried to learn about the social and political environment for scientists during the late 19th century. Pogson also happens to be an expert asteroid discoverer and there were some interesting coincidences between his life and my life. The whole work has recently been accepted for publication for a 40 page peer-review journal article by the Journal of British Astronomical Association and is expected to be published soon. The main reason I want to give this talk is to show how scientists can also do very good social science research and the skills you learn by doing so will be very valuable in your own research area.

Anna Springsteen, M.S. student – From Grassland to Woodland: A 42-year Chronosequence in Mandan, ND (February 23, 2007)

Woody plant expansion, in which shrub abundance increases at the expense of grasses, is an issue for grasslands worldwide. In North Dakota, both rare mesic prairies in the east and semi-arid grazing lands in the west display this shift in plant life form dominance. Increased aboveground heterogeneity is often observed during a vegetation shift, but belowground changes in soil qualities can also occur and have been documented in the American southwest. Few studies on woody plant expansion have been done in northern, semi-arid grasslands. As such, the objectives of this study were to (1) assess the differences in belowground carbon and nitrogen pools associated with woody plant expansion over a 42-year chronosequence in a grassland in the Northern Great Plains and, if so, (2) determine if there were any trends. Soil samples were collected in Mandan, North Dakota within a reserve rangeland owned by the Northern Great Plains Research Laboratory of the ARS-USDA. Samples were analyzed

35

for total carbon and nitrogen, etc. at three depths (0-5 cm, 5-10 cm, and 10-15 cm) along a 42-year chronosequence of woody shrub encroachment.

Inga Foster, M.S. student – Odonata Diversity and the Glacial Ridge National Wildlife Refuge (March 2, 2007)

The first survey of dragonfly and damselfly diversity was conducted at the newly established Glacial Ridge National Wildlife Refuge in northwestern MN. Site-collected Odonata (dragonflies and damselflies) were identified and used to construct a Glacial Ridge local species pool. A predicted regional species pool was modeled using Maxent. The first results of this research support the species pool hypothesis: the local species pool was contained within the regional species pool.

Tedros Berhane, M.S. student – Remote Sensing of Heat Flux (March 30, 2007)

My research topic emphasis on comparing aET (actual evapo-transpiration) modeled using data obtained from Landsat TM and Terra MODIS, and a surface energy balance algorithm for land (SEBAL) model. My talk will generally cover, what is ET (evapo-transpiration), why it is important to measure, what are the different approaches used to measure ET. Specifically how SEBAL, a model that works on surface energy balance approach is used in my study to estimate aET. Comparison of result will be included between modeled and measured heat fluxes over Brookings and Black Hill flux towers, validation sites for my modeling result.

Andrei Kirilenko, ESSP faculty – Predicting Climate Change Impact on Insect Biodiversity: Comparison of Scenarios (April 13, 2007)

The rate of current climate change during this century is likely to be faster than during any time within the last ten millennia. One of the expected impacts of the changing temperature and precipitation pattern is a shift of current insect ranges, with likely negative consequences for insect biodiversity. This effect is expected to be especially strong in fragmented agricultural landscapes found across the North American continent. There is, however, a critical gap in our understanding of the climate change impacts on insects, even though the insects are the most ecologically dominant group on the planet, and the changes in dominant species are likely to provide numerous feedbacks, mitigating or amplifying climate change impacts. One of the reasons little is known about future distribution changes in insects is that the absolute majority of studies employ just one or a few future climate projections. Given the stochastic nature of climate and uncertainty in future radiative forcing, it is rendered virtually impossible to ascertain the likelihood of isolate effects. I compared the outcomes of a large set of the General Circulation Models (GCMs) predictions of the future climate, presumably covering 95% of the entire range of GCM simulations. I further modified GCM results to include both interannual and daily variability, which increased the number of climate ensemble members considered to around 20,000. During the seminar we will informally

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discuss generation of the climate layers, GCM integrations, MaxEnt model used for simulation, and simulation results.

Lijian Shi, Visiting student – Use of Satellite Synthetic Aperture Radar Imagery to Map Oil Spills in the East China Sea (April 20, 2007)

Oil spills are one of major environmental concerns especially in the costal zones of the World Ocean. Synthetic Aperture Radar (SAR) imageries from the ERS-2 and Envisat satellites are proved to be a useful tool for monitoring oil spills in the marine environment due to all-weather and all-time capability. A set of 120 SAR images acquired over the East China Sea in 2002-2005 have been collected, processed and analyzed with respect to oil spills. To properly analyze SAR image signatures of oil spills a geographic information system (GIS) as a framework has been chosen. The oil spills distinguished from look-alike phenomena by using other remote sensing data and contextual information were incorporated into GIS to get finally the oil spills distribution map for the East China Sea. Analysis of the temporal and spatial distribution of the oil spills revealed the risk areas and confirmed previous findings that oil spills are mainly distributed along the general ship routes. That verifies that illegal discharges from ships are main source of oil pollution in this region. The detailed analysis also revealed different types of oil pollution and showed diurnal and seasonal variations of amount of oil spills detected on SAR images acquired in summer/winter.

Leigh Ciofani, M.S. student – Woody Shrub Encroachment in North Dakota Grasslands: Using Predictive Modeling to Examine Key Players and Management Implications (April 27, 2007)

Woody shrub encroachment is one of the major threats to grasslands, tied to other factors such as fire regimes, herbivore grazing patterns, and climate; encroachment is currently a global trend. Consequences of woody encroachment can significantly impact many of the ecological characteristics of grasslands. Studies conducted on grassland ecosystems have pointed to grassland management, in the form of prescribed burning, grazing, or some combination of the two, as a way to prevent woody encroachment. Prevention of encroachment may be particularly important to preserving grasslands, as management may not be effective in reducing shrub coverage once woody species have become established. Knowledge of the geographical distributions and names of woody shrub species that are possible encroachment threats is lacking; such predictive distributions are needed to identify likely problem species and indicate where they could occur. Predictive niche modeling could provide a way to hypothesize whether or not certain woody species could pose encroachment problems in selected grasslands. This would aid management efforts aimed at preventing woody encroachment by recognizing species of major concern before they become established in these grasslands.

Leigh Ciofani, M.S. student – Predictive Distribution Modeling: An Introduction to the Details (September 28, 2007)

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Predictive modeling of species distributions is a central aspect of my thesis research. Before beginning my thesis, I was aware of the basic concepts of predictive modeling, but as my research progressed I became more aware of some of the fundamental issues involved in this area of research. This presentation is an introduction to some of the areas (model methods, assumptions, input data, and limitations) I considered when developing my thesis research methods.

Sherry Fieber-Beyer, Ph.D. student – Spinel-Bearing Asteroids… The Most Ancient Asteroids in the Solar System (October 5, 2007)

Introduction: Four spinel-bearing asteroids have been iden-tified in the mainbelt. These asteroids are distributed across the asteroid belt, implying they are not fragments of a common dis-rupted parent body. The spinel contained within these asteroids appears to be embedded in calcium aluminum inclusions (CAI’s) much like that of the CV3 chondrite Allende [1]. Their preserva-tion implies a lack of igneous processing and places further con-straints on the heating that occurred within the early solar system. This study analyzes the four known spinel-bearing asteroids: 980 Anacostia [1], 387 Aquitania [1], 755 Quintilla [2, 3], and 234 Barbara [4]. Conclusions: The sine i vs. semi-major axis graph indicates that the distribution of spinel-bearing asteroids within the main-belt is not consistent with these bodies being derived from a sin-gle parent body. We propose these asteroids come from three different parent bodies with the exception of 980 Anacostia and 387 Aquitania, which have been previously proposed as having been derived from the same parent body [1]. The spinel within the asteroids is most likely refractory spinel grains embedded in CAI’s. In order to be spectroscopically detected, the spinel-bearing CAI’s must make a significant fraction of the asteroid surface material, indicating CAI concentrations several times that found in CV3 chondrites such as Allende. In order to achieve this concentration, the parent bodies must have formed at an early time when CAI’s still represented of substantial fraction of the grains that had formed in the cooling solar nebula. Alternately, parent body accretion may have occurred somewhat later in re-gions where dynamical processes had concentrated CAI’s. We propose these spinel-bearing asteroids are the most ancient aster-oids in the solar system and that they were the first large bodies to accrete out of the cooling nebula. Investigation is still ongoing concerning 234 Barbara as a potential candidate supplying the ν6 resonance with asteroidal fragments.

Tedros Berhane, M.S. student – Remote Sensing of Heat Fluxes: Validation and Inter-sensor Comparison (October 12, 2007)

Accurate estimate of evapotranspiration (ET) is critical in understanding and monitoring the dynamics of water and energy. Evapotranspiration has been indirectly estimated using various methods. Of all the methods, surface energy balance method has an advantage in providing ET estimate at different spatio-temporal scales whereas most of the other methods have been regarded as labor-intensive and require highly skilled operational stuffs and / or need substantial financial resources for operation and maintenance.

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Instantaneous heat fluxes were modeled using data obtained from Landsat 5 TM (Thematic Mapper), Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) using Surface Energy Balance Algorithm for Land (SEBAL) model for cloud-free days. The modeled results were compared with measurements by two flux towers located in Brookings, SD and Fort Peck, MT.

SEBAL performed better in modeling the heat fluxes when Landsat data was used than MODIS. It is believed to be due to scaling issue; because the footprint areas (an area in the upwind direction of a flux tower that would contributes to the flux tower measurement) have always been significantly less than a single MODIS pixel. By simulating MODIS observation using Landsat, it is found that the correlation coefficients for the aggregated Landsat pixels decreased .This suggested that poor performance of MODIS estimate of heat fluxes as compared to the flux tower measurements is due to heterogeneity of surface within a field of view.

Gordon Akudibillah, M.S. student – The Effect of the Use of Resistant Cultivars on the Evolution of Tomato Leaf Curl Virus (TYLCV) (November 2, 2007)

The use of resistant cultivars to manage crop pathogens lies in the heart of sustainable agriculture. However, the relative effects these resistant cultivars have on the evolution of the pathogens are unknown. I will employ the use of mathematical models and the concept of Evolutionary Stable Strategies (ESS) to explore the effect of the use of resistant cultivars on the evolution of Tomato Yellow Leaf Curl Virus (TYLCV)

Vishnu Kanupuru, Ph.D. student – Made for Each Other?: Binary Asteroids in the Solar System (November 16, 2007)

An informal summary of our current knowledge of binary asteroids in the solar system. The highlights include why are binary asteroids important, binary asteroids and evolution of life on earth, how are binary asteroids formed, how to discover binary asteroids, etc.

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ASSESSMENT TOOL #7:

STUDENT ANNUAL EVALUATIONS FROM THE DEPARTMENT All ESSP students receive an annual evaluation that is composed of three data sources. These include: 1) statement from each student, 2) completed evaluation matrix from each student’s GRA supervisor, and 3) completed evaluation matrix from each student’s major professor. All data sources are compiled and summarized into a review letter that is given to the student. The review rubric (Figure 1) includes numerous evaluation areas, including a) quantity of work, b) quality of work, c) teamwork, d) initiative/resourcefulness, e) leadership, f) dependability, g) attendance, h) communication skills, i) knowledge of specific area of study, and j) overall knowledge of Earth System Science/Policy. Each student’s major professor and GRA supervisor complete the review rubric.

Figure 1. Review rubric used in student annual evaluations from the department.

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Summary of Results

0102030405060708090

100

Overall evaluation scores of the students - 2006

0102030405060708090

100Quantity of Work

Quality of Work

Cooperation

Initiative

Leadership

Dependability

Attendance

Communication Skills Verbal

Communication Skills Written

Specific knowledge

Overall knowledge

Overall Evaluation

Overall evaluation scores of the students - 2006

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0102030405060708090

100

Percentage of students with scores above 75 (Good to Excellent) - 2006

0102030405060708090

100

Percentage of students with scores less than 50 (below Satisfactory) - 2006

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0102030405060708090

100

Percentage of students with scores less than 50 (below Satisfactory) - 2006

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ASSESSMENT TOOL #8:

GROUP DATA FROM STUDENTS All ESSP students are invited to and encouraged to attend regular programmatic focus groups, typically involving a free lunch for the students. These focus groups generally occur every six weeks or so, and involve at least one ESSP faculty member. Typically, three fundamental questions are asked: 1) What aspects of the program do you like the most and why? 2) What aspects of the program would you like to see improved or discontinued? 3) How prepared do you feel to move on to the next phase of your career?

Summary Comments from 2006-07 Focus Groups

“I would prefer to see the large ESSP 501 and 502 class structure broken up along block lines. This would then allow potential employers to get an idea of the breadth of activities conducted in each class rather than just seeing a single class listed on my transcript.” “The website needs to be updated.” “Having 7-10 students in ESSP 501 and 502 would be ideal. Fewer than seven is probably too few, while larger than 10 might mean less attention from the instructor to individual students.” “I like working with faculty members on their research projects. I’ve learned a lot, while also getting some great experience.” “Dr. Hanley teaches a very organized block. I learned a lot.” “I like the support that I receive from the department. A GRA, tuition waiver, and now a free lunch. What else could a graduate student ask for?” “More elective classes should be offered from the ESSP program.” “I suggest adding 1 or 2 more environmental policy faculty members to the ESSP faculty. Policy seems to be pretty weak compared to the science side.” “The team projects are a real challenge, and the peer evaluations should be discontinued.” “ESSP should offer an Environmental Ethics course.” “Even though I really don’t like working in the geospatial lab, I know I’m learning some cool skills that employers will be looking for.” “There isn’t enough management in the Masters of Environmental Management degree.” “Dr. Hill should prepare his own lectures and not use presentations from the web.”

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“Dr. Hill’s block project was the best so far.” “I don’t understand how the department relates to the Northern Great Plains Center for People and the Environment.” “The ESSP faculty always seem to be available for discussion.” “My friends in other departments have been complaining about having their tuition waivers reduced, but mine was just fine. I like the way the department takes care of me.” “The program is demanding, but good.” “I would like to see graduate teaching assistantships available. I would especially like to gain some teaching experience before I graduate.”

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ASSESSMENT TOOL #9:

EXIT INTERVIEW DATA FOR GRADUATES AND STUDENTS LEAVING THE PROGRAM

All students graduating from or otherwise leaving the program give an exit interview to the chair. Each interview typically involves at least three questions. These include: 1) What did you like the most about the ESSP program and why? 2) What did you like the least? 3) What would you change about the program that would have made your learning experience better? Summary Comments from Exit Interviews

“I very much enjoyed my time here in the ESSP program and UND. Without the education and experience I gained in the program, I could have never landed the job I did.” “All of the faculty members were very supportive during my time here. My major professor spent many, many hours working with me as I was nearing completion of my thesis.” “I think I liked the comradery among the students was one of the best things about the program. I learned more from discussions that I did from lectures.” “The team projects are especially valuable when I went for job interviews. All of the interviewers asked me what experience I had working in teams to accomplish goals. I was able to say that I had loads because of what the ESSP program offered.” “I liked the fact that there are so many women students in the program. Most science program across UND that I’m familiar with have very few women, but ESSP seems to really make an effort to recruit women.” “The ESSP website seems to be way out of date.” “There definitely needs to be more policy classes and expertise in the program. One or two more policy faculty members would be great.” “I wasn’t a big fan of working in the geospatial lab. I never had the idea that I was contributing to anything bigger.” “I wish I had a larger desk for my stuff during my time here.” “I think it’s important to maintain a level of high quality students admitted into the program. In my opinion, there were a couple of students who probably should not have been admitted and who later dropped out of the program. I see the overall quality and health of the program as being directly linked with me after I leave.”

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“There is a very nice international component to the ESSP faculty. I might be nice to hire a couple more Americans to teach in the program who have more direct experience with science-related issues in the U.S.” “I didn’t know what to expect when I first arrived in grand Forks. ESSP 501 was a real culture shock for me. Those classes taught to manage time like I never have before. All in all, I liked it.” “I didn’t really like the peer-evaluations in ESSP 501 and 502. I felt like I was responsible for determining the grades of my fellow classmates.” “Everyone in the program was very helpful to me. I especially liked working with Xiaodong, and the other members of my committee.”

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6.0 Closing the Loop: What We Learned Based on an evaluation of the assessment data, several issues were highlighted that affirm achievement of student learning goals and identified areas for change. These include: Assessment Tool #1: Completion of whole fundamental courses, i.e. ESSP 501, ESSP 502. The pass rate of students through these courses is near 100%; however, one student during the past year dropped out of ESSP 502 after stating that he just was not dedicated to the rigorous program and to science in general. One recent graduate of the ESSP program described the 501/502 suite of classes as “academic boot camp” which tests a student’s dedication to general scholarly activities and working together in student teams. Nevertheless, all of the students who have completed these courses pass them with either and “A” or “B” and display significant growth in their overall academic skills. Assessment Tool #2: Course evaluations. We learned that the quality of instruction within the ESSP program varied from professor to professor; however, a majority of students thought their learning experiences were useful in professional development and interesting overall. In comparison to all graduate-level courses at UND, ESSP courses were above average in the following categories:

1. Availability of faculty to students 2. Improvement of oral and written communication skills 3. Improvement of familiarity with different cultures 4. Readings and assignments contributed to learning 5. Effectively used technology in teaching 6. Instructor effective in promoting my learning

Areas identified for improvement include:

1. Instructors finding ways to keep students interested 2. Explaining grading criteria clearly 3. Helped students connect ideas, events, or knowledge 4. Work appropriate for credit given 5. Instructors communicating ideas clearly

As a response, we held an annual ESSP curriculum review workshop in August. During this workshop, all faculty members presented a general overview of their block, including material covered and teaching methods employed. This workshop also served to help standardize how the material is presented across the ESSP curriculum with numerous new ideas being presented and employed. Assessment Tool #3: Assignment to and progress towards completion of a faculty-advised research project.

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We learned that most students were readily able to make progress towards their assigned research projects. A minority of students did not possess the needed skills to make immediate contribution to the assigned projects. These lack of skills included poor English skills, poor statistical skills, poor writing skills, and poor literature searching skills. As a result, remedial exercises have been developed for these students to help them correct observed deficiencies. These exercises include literature searching instruction, drafting research reports, and working on simple statistical problems. Assessment Tool #4: Regular reviews of student progress by student’s graduate advisory committee and the UND Graduate School, i.e. comprehensive exam, research proposal, thesis defense, etc. We learned that students who get started early in their programs making progress towards completion of these requirements perform significantly better as graduate students than students who procrastinate in completing these requirements. As an example, students who form their advisory committee by the stated deadline of the ESSP program and the Graduate School were vastly superior as students from those who did not. In fact, two recent students who did not form their committees by the end of their first year ended up dropping out of the program. As a result, specific instruction has been given to all ESSP faculty members stating the required deadlines of the ESSP program and the Graduate School. Additionally, extra emphasis is now being given to student applications to avoid recruiting students who are not likely to complete their degree programs if admitted. Assessment Tool #5: Participation in scholarly conferences. We learned that students very much enjoy participating in these activities even though they commented on a sense of anxiety from giving public presentations. We have had students present at international, national, regional, and local conferences. The UND Scholarly Activity Forum is noted as a favorite among students due to the networking opportunities within their own university and the possibility of getting attention for their work from upper-level administrators of UND. Assessment Tool #6: Participation in the department’s brown bag luncheon seminar series. We learned that these seminar opportunities have been welcomed by the students as an excellent way to practice presentation skills and receive ‘friendly’ feedback for their work. As a result of feedback about these seminars, the department pays for pizza at every other seminar or so as a way to encourage attendance. Assessment Tool #7: Student annual evaluations from the department. We learned that overall student performance in GRA work ranged widely from outstanding (most) to mediocre (very few). As a result, those students who were rated poorly received detailed feedback about their performance and a one-on-one conversation about their overall performance from their major professor. These evaluations will likely play a central role in the assignment of student tuition waivers in the future.

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Overall, areas of strength among students are ranked as:

1. Attendance 2. Quality of work 3. Quantity of work 4. Dependibility

Overall, areas identified as needing improvement among all students evaluated are ranked as:

1. Leadership 2. Cooperation 3. Communication skills 4. Specific knowledge of research area

Assessment Tool #8: Group data from students. We learned that students that students prefer to have the ESSP 501/502 block structure broken up into separately listed courses. Several important reasons were given for this including having true representation of the material covered listed separately on student transcripts. It is believed that by listing each block separately on transcripts, students will be more competitive for employment opportunities. Additionally, if a student does poorly in one block, then the possibility exists that the entire semester would need to be retaken for credit, including those blocks where passing grades were earned. We are in the process of drafting a request to break the ESSP 501/502 blocks into separately listed courses. This request will likely be submitted through the appropriate channel sometime in 2008. Assessment Tool #9: Exit interview data for graduates and students leaving the program. We learned that students exiting the ESSP program greatly appreciated their overall learning experience at UND. Every graduating ESSP student so far has accepted a job offer or Ph.D. position before they left UND, which almost certainly contributed to overwhelmingly positive feelings towards the program. Even students who left the program without graduating had very positive things to say about the program and the help they received will they were students. One recurring suggestion from graduating students is the desire for more policy-orientated faculty members in the ESSP program and a greater policy component to the overall ESSP curriculum.

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7.0 Closing the Loop: Actions Taken

As a result of the data from our assessment activities and the lessons learned from them, numerous curricular and research changes have results over the past year. These include:

1. A proposal to break the blocks from ESSP 501 and 502 into individual courses is

currently being developed. This proposal will be finalized and submitted through the appropriate channel in 2008.

2. Offering ESSP elective courses in the summer semester. This change resulted from numerous suggestions from students that they could not fit ESSP elective courses into their programs of study when they are offered during either the fall or spring semesters. These semesters are dominated by the ESSP 501/502 suite of courses.

3. In faculty-advised projects, students are now encouraged to develop these projects into their thesis projects for M.S. students. This change will hopefully lead the students to take greater leadership and ownership of these projects and develop a sense of overall responsibility towards them.

4. The next faculty hire within the program will be a policy-related in his or her research emphasis.

5. ESSP faculty members are now required to develop a full syllabus for his or her respective block responsibilities, which will include detailed explanations of the grading scheme. Additionally, one faculty member will be identified as being responsible for either ESSP 501 or 502. This faculty member will be responsible for coordinating activities among the different faculty members involved and uploading the final grades for the semester.

6. Greater emphasis will be given to recruiting a balance between M.S., M.E.M., and Ph.D. students.

7. All faculty members are required to meet at least once every two weeks with students under their guidance. These meetings are intended to insure adequate progress is being made towards research projects, program of study, and to intervene in any developing problems when necessary.

8. An evaluation form has been developed for the supervisors of M.E.M. student internships. Previously, there was no method by which supervisors of ESSP interns could have formal input into the final approval of a student’s internship. With this change, the advisory committee of each M.E.M. student can now use the internship final report (from the student), final presentation (by the student), and final evaluation (from internship supervisor) as a basis for final approval of the internship.

9. Student GRA work in the geospatial lab has been reorganized into specific projects with outcomes that can be used to more fully measure student success.

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10. All ESSP students are regularly encouraged to participate in scholarly conferences as

often as possible. The UND Graduate School Conference has been used regularly by both faculty and staff.

11. All students are required to given at least one departmental brownbag seminar during their time in the ESSP program. Most students readily embrace this opportunity; however, a few students need this requirement to participate in this seminar series.

12. More opportunities are being developed to enhance student leadership skills. These include: updating the ESSP website, giving guest lectures in classes, running student labs, and serving as informal student mentors.

13. More team-orientated activities are being developed for in-class projects and projects in the geospatial lab. Data show that teamwork skills are the number one most sought after skill among potential employers of ESSP graduates. Teamwork is also one of the least developed skills among incoming ESSP students.

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Appendices 1-24. Sample Individual Class Assessment Tools from ESSP Courses Appendix 1. The Effect of Climate Change on Biodiversity of North America block capstone project ……….….. 55 Appendix 2. CO2 in the Atmosphere- A Historical Look Biogeochemistry Lab ……...…………………………… 56 Appendix 3. Sustainability Communications Capstone Project ……………………………..…………………….. 63 Appendix 4. Research on the Mind lecture, discussion, and lab assignment ………………………..…………….. 66 Appendix 5. Global Temperature Change Biogeochemistry Lab ………………………………...………...........… 80 Appendix 6. Environmental Advertisement Analysis ……………………………...………………………………. 84 Appendix 7. Species Predictive Distributional Modeling …………………………………...……………...……… 85 Appendix 8. Micro-Economics of Bottled Water …………………………………………..……………………… 93 Appendix 9. Full Cost Accounting Analysis of a Hypothetical Landfill ………………………………………...… 94 Appendix 10. Biological Diversity Policy Debate ……………………………….……….………………………. 101 Appendix 11. Full Cost Accounting Assignment Involving Solid Waste Management and the Issue of Landfilling

Waste ………………………………………………………………………………………………. 102 Appendix 12. Course Capstone Communications Paper & Presentation ………………………………………… 104 Appendix 13. Non-Market Valuation of Biodiversity Using Non-Traditional Valuation Methods ……………… 107 Appendix 14. Introduction to GIS – Biosphere Block Lab ………………………………………………………. 109 Appendix 15. Advanced GIS Applications Lab ………………………………………………………………….. 127 Appendix 16. Communications Analysis Poster Presentation ………………………………………………...…. 134 Appendix 17. Nature-Based Tourism in the Pembina Gorge, North Dakota ………………….…………………. 136 Appendix 18. Media Advisory: Climate Experts Can Comment on ‘The Day After Tomorrow’ – A Science Review

………………………………………………………………………………………………..…….. 137 Appendix 19. Advanced GIS Measurement Lab …………………………………………………………………. 139 Appendix 20. Scientific Journal Student-Led Discussion ………………………………………………………... 145 Appendix 21. Building Bridges – The Purpose of Earth System Science – An Example From the Hydrologic Block

…………………………………………………………………………………………………...…. 147 Appendix 22. Movement of Crop Material From One Year to Another …………………………………………. 149 Appendix 23. Letter to the Editor Assignment …………………………………………………………..…..…… 152

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APPENDIX 1

Department of Earth System Science and Policy Earth System Science and Policy I (ESSP 501, 501R, 501L)

Block II: Biosphere’s Productivity Cycle-Dr. Hanley Block Capstone Team Project Description: Fall 2005

THE EFFECT OF CLIMATE CHANGE ON THE BIODIVERSITY OF NORTH AMERICA

TO: Northern Great Plains Climate Change/Biodiversity Research Group FROM: Kofi Annan, Secretary-General of the United Nations (UN) Dear Research Group:

The United Nations is in a never-ending race to make the world a better and safer place to live. The Division for Sustainable Development provides leadership and is an authoritative source of expertise within the United Nations system on sustainable development. Our goal is the integration of the social, economic and environmental dimensions of sustainable development in policy-making at the international, regional and national levels. For the same purpose, I am requesting premier organizations in various regions of the world to provide us with feedback of the effect of long term climate change on various life forms.

Specifically, I need to know the following:

• A generalized background to climate change projections as depicted by the Hadley Model for the years 2050 and 2080

• How might climate change effect the distribution of Mammals, Microbes, and Flora in North America and across the world (you can pick up one distinct type from each category)

• What are the policy recommendations you would like to suggest concerning this distribution due to climate change keeping in mind the goal of sustainable development

I will require a written policy recommendation, formal presentation, and a policy

brief (including a script that could be used as a basis for a television information spot). My highly valued scientific and political advisors, Drs. Hanley, Tyndall, and Laguette will provide you with any additional details you might need. Please submit the required materials by the deadlines outlined by Dr. Hanley.

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APPENDIX 2


Block IV: Biogeochemical Cycle Spring 2005-Hanley

LAB 2: CO2 IN THE ATMOSPHERE – A HISTORICAL LOOK 1. Introduction

The scientific community has reached a strong consensus regarding the science of global climate change8. The world is undoubtedly warming. This warming is largely the result of emissions of carbon dioxide and other greenhouse gases from human activities including industrial processes, fossil fuel combustion, and changes in land use, such as deforestation. Continuation of historical trends of greenhouse gas emissions will result in additional warming over the 21st century, with current projections of a global increase of 2.5ºF to 10.4ºF by 2100, with warming in the U.S. expected to be even higher. This warming will have real consequences for the United States and the world, for with that warming will also come additional sea-level rise that will gradually inundate coastal areas, changes in precipitation patterns, increased risk of droughts and floods, threats to biodiversity, and a number of potential challenges for public health.

How did the scientific community come to such dire conclusions? Is it possible to

obtain a look at composition of Earth’s atmosphere before humans were able to take direct measurements? Ice core samples provide an uninterrupted source of data on important properties of paleoclimate, including local temperature and precipitation rate, humidity, and wind speed. Ice core samples also record changes in atmospheric composition. In this lab we will work with the original data from the famous Vostok Ice Cores, which carry the distinction of being the only ice cores that scientists are certain have remained undisturbed for the last interglacial and penultimate glacial periods9.

2. The Vostok Research Station

The Vostok research station is located near the south geomagnetic pole, at the center of the East Antarctic ice sheet, where the flux in the earth's electromagnetic field is manifested. It has the dubious distinction of being the coldest place ever recorded on the planet (-91°C or -131.8°F in 1997). The station was built in 1957 and named after one of the ships of F. G. von Bellinghausen, one of the original discoverers of Antarctica.

8 National Academy of Sciences, Commission on Geosciences, Environment and Resources., 2001. Climate Change Science: An Analysis of Some Key Questions. National Academy Press, Washington, D.C. 29 pp. 9 AGU, 1995.

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The Vostok research station has operated year-round for more than 37 years. In

the 1970s, researchers from the Soviet Union drilled a set of holes 500–952 m deep in the ice. These holes have been used to study the oxygen isotope composition of the ice, which showed that ice of the last glacial period was present below about 400 m depth. Three more holes were then drilled: in 1984, Hole 3G reached a final depth of 2202 m; in 1990, Hole 4G reached a final depth of 2546; and in 1993 Hole 5G reached a depth of 2755 m. Currently, a Russian, French, and American team of scientists is drilling an ice core through the 3,700 m thick ice sheet. The ice at the bottom of this core is estimated to be half a million years old. 3. Ice Core Samples

Ice cores are unique with their

entrapped air inclusions enabling direct records of past changes in atmospheric trace-gas composition. Ice samples are cut with a band saw in a cold room (at about -15°C) as close as possible to the center of the core in order to avoid surface contamination. Gas extraction and measurements were performed, which involved crushing the ice sample (~40 g) under vacuum in a stainless steel

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container without melting it, expanding the gas released during the crushing in a pre-evacuated sampling loop, and analyzing the CO2 concentrations by gas chromatography. LAB ASSIGNMENT

In this lab, you will analyze the original CO2 data from the Vostok ice core samples and answer a series of questions.

Part 1. Ice and CO2 in the Vostok Core

First, download the primary data file containing the Vostok ice core data (Public

Drive/ESSP_Public/Biogeochemical Block/Lab-CO2 in the Atmosphere…/vos_data.tsv). Save it onto your hard drive as a worksheet entitled: vosdata. Note: open the file in Excel (you may need to specify files of type: “All Files”). The data should be imported as delimited and tab-separated. Your Excel sheet should contain the following columns: depth (in meters) of the ice core, the “ice” and “gas” ages (in thousands of years), concentrations of CO2 and CH4 found in the ice bubbles, the deuterium isotopic ratios, and a column that provides information on dust. If you do not have this right now, then go back and try again.

The ice age (i.e. the age of the ice, which should not be confused with the use of

the term ice age as referenced by an ice sheet that moved down over northern latitudes a few thousand years ago) is obtained by counting layers of ice and modeling the flow of merging ice layers. The gas age is calculated assuming that the bubbles of gas can only be trapped effectively in layers of older ice (i.e. at a depth well below the surface where the pores of the ice close, thus sealing the air).

Now, you will plot both ice age and the gas age as a function of depth. First,

select the entire ice age column by clicking on “B” at the top of it, then hold down the control key, and then select the gas age column by clicking on the “E” at the top. Once both are selected, click on the “Chart Wizard” icon and select the first line graph (without markers) option. In step 2 of the “Chart Wizard”, modify the series data (click on the series tab) to use the depth values in column A as the category (X) labels. You will need to specify the numbers themselves, not the whole column. The formula for the X values for both series should look like this: =vos_data!$A$3:$A$196. Now click “Next,” and give your chart appropriate labels for the title and axes. Be sure to label appropriate units. If you do not know what they should be, then re-read this lab from the beginning. You should always know what you are graphing and why! Next, finalize your chart and print it out (full page) to turn with your answers to questions. [3 points]

Questions 1. The two age curves differ. Why? How much younger, roughly, is a bubble of

gas than the ice that surrounds it, and a depth of 1000 meters? [2 points]

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Part 2. The Temperature Record

Ice in glaciers has an increased proportional abundance of heavy oxygen if it was deposited during relatively warm periods. To understand why this might be so, think about the process of glacier formation. The water-ice in glaciers originally came from the oceans as vapor, later falling as snow and becoming compacted in ice. When water evaporates, the heavy water (H2O18) is left behind and the water vapor is enriched in light water (H2O16). This is because it is harder for heavier water molecules to overcome the barriers of evaporation. Thus, glaciers are relatively enhanced in O16, while the oceans are relatively enriched in O18. This imbalance is more pronounced in colder climates than for warmer climates. In fact, it has been shown that a decrease of one part per million O18 in ice reflects a 1.5°C drop in air temperature at the time it originally evaporated from the oceans.

Now we want to convert the deuterium isotopic ratios to temperature changes (∆

temperature) that describe variations in the temperature of the ocean from which the ice was originally evaporated. Use Excel to do this and work up a new column. Type “delta temp” in the first row of your new column and “(deg C)” in the second row. Now use Excel to calculate the ∆ temperatures, filing your new column (use the Excel help menu if you do not know how to do this). Highlight the column and give the numbers two decimal places. Use the following relationship:

Type “= (C3 + 440) / 6.2” into the first cell, then put the cursor on the lower right corner of the cell until it turns into a cross. Click and hold the left mouse button and drag down to the end of the column. The cursor applies the relationship of the first cell to other cells.

Save your work. Think about why the ∆ temperatures change with deuterium isotope ratio in the way they do.

Plot the ∆ temperature curve as a function of ice age (use either a line or scatter

plot) and incorporate into your report. [5 points]

Questions 2. By how many degrees has climate varied in the past, as indicated by these data?

[1 point] 3. Approximately when were the last glacial and interglacial periods? Within the

most recent glacial period, what were the highest and lowest ∆ temperatures? What do you think Grand Forks might have looked like during these times? [3 points]

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Part 3. The Atmospheric Composition and Dust Record

Use the following scatter plots of CO2 and CH4 concentrations, as well as ∆ temperature and dust as a function of (ice) age, to answer the questions for this section. These were made from the same data you are using, and you may want to replicate them yourself to get more practice with Excel. Note: for plotting ∆ temp on your graph, place that data on the “secondary axis.” [no points awarded, but I encourage you to make them nevertheless]

CO2 & CH4 Concentrations, Plotted with ∆ Temperatures

0

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1 14 27 40 53 66 79 92 105 118 131144157 170 183

Age of Gas/Age of Ice (ka)

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CO2 ppmvCH4 ppbv∆ Temp (deg C)

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Questions 4. Note the time of the two major warming events. Then look at how CO2 and CH4

change during the same time. From the data provided in this lab, can you tell which changes first, temperature or greenhouse gas (CO2, CH4) composition? Suggest reasons why it could work either way. [2 points]

5. These graphs do not show recent values. Think of several reasons why CO2,

CH4, and dust concentrations were different during glacial time as compared to the 18th century, and predict how the Industrial Revolution might have affected the global concentration of CO2 and CH4. [2 point]

Part 4. What Does All This Tell Us About Climate Today?

First, add another column to your Excel file to estimate the temperature at Vostok. Label this column Vostok Temp. (deg C). To do this, simply subtract 55.5 degrees from the values in the ∆ temperature column to get an estimate of the temperature at Vostok itself.

Create scatter plots (without connecting lines) of CO2 vs. temperature and CH4

vs. temperature using the Vostok data. Note: again for plotting ∆ temp on your graph, place that data on the “secondary axis.” Next, use the Insert a linear “trend line” and report the equation and r2 value by checking those boxes in the option menu for trend lines of each scatter plot in your lab report. [3 points each]

Dust & Temperature as a Function of Age

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1 15 29 43 57 71 85 99 113127 141 155 169183


Dus

t Con

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Questions 6. Why is the r2 value for CO2 or CH4 less than one? [1 point] Extra Credit Predict the temperature of Vostok today. Use today’s CO2 concentration (360 ppmv) to solve the linear regression equation from the past relationship between CO2 and temperature. How does this calculated temperature differ from the surface temperature today at Vostok? Explain why these might be different. [3 points] Additional Readings Monnin, E., A. Indermühle, A. Dällenbach, J. Flückiger, B. Stauffer, and T. F. Stocker. 2001. Atmospheric CO2 concentrations over the last glacial termination. Science, 291: 112-114. Petit, J. R., J. Jouzel, D. Raynaud, N. I. Barkov, J. M. Barnola, I. Basile, M. Bender, J. Chappellaz, J. Davis, G. Delaygue, M. Delmotte, V. M. Kotlyakov, M. Legrand, V. Lipenkov, C. Lorius, L. Pépin, C. Ritz, E. Saltzman, and M. Stievenard. 1999. Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica. Nature, 399: 429-436.

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APPENDIX 3

Department of Earth System Science and Policy Communicating Environmental Information (ESSP 570)

3 Credit Hours, Hanley Fall 2005

Capstone Project

The capstone project for ESSP 570 is designed to provide you with an opportunity to integrate the knowledge and skills you have acquired throughout this course into a single project. You will select an environmental communication issue that will serve as the topic of your project. You have considerable latitude in your selection; however, I am looking for an analysis of the communication issues of your topic, not necessarily of conceptual issues associated with it. You must get approval of your chosen project theme.

There are three parts to your final project:

a) A final paper b) A final presentation (PowerPoint format preferred) c) A personal statement dealing with the process of formulating your project

Final Paper:

The final project should be an interesting, complete and an efficient way to present your communication issue and strategic approaches for communicating your chosen issue to your selected audiences.

You must include the following in your paper: 1. A review of the background issues, including a statement of need. 2. A discussion of the objectives of your project with a clear rationale for choosing

these objectives. 3. A clear statement and rationale for your choice of target audience(s). Why these

folks? 4. What key questions did you have about your audience(s) and what information did

you gather about your target audience? How did you gather it? What are the strengths and limitations of what you know about them?

5. Clear presentation of your communication strategies. What principles of

communication are you recommending and why?

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6. Specific examples - this should include central messages, possible examples of print

or other media. 7. Delineation of how the plan will be evaluated. 8. Recommendations: how the client can use this information; how future students may

build on your work.

A possible, but not mandatory, format for the paper:

Title page Acknowledgements (optional) Executive summary Table of contents Introduction Body (See major points above) References Appendices (as necessary)

References must follow the publication style of the Professional Communication

Style (http://www.ieeepcs.org/activities_publications_transactions_authors.php). Any source which appears in the text must appear in the bibliography.

Your papers should be no more than 20 pages and can include visuals and ancillary information in an appendix. All projects must be submitted by Friday, December 9, 2005. That deadline is set in stone, no exceptions, no extensions. Final Presentation:

The final in-class presentation will be to your peers and to clients who are attending. There may be other students working on similar topics who may choose to attend as well. Your presentation should be roughly in the same format as your paper. Your presentation should not be designed in a discussion format, but rather a full presentation with questions/comments at the end. Please ask me if you have any questions as to the format of your presentation.

Personal Statement:

In addition to a final paper and presentation, you are required to write a short description of your personal observations during the course of your project. You are encouraged to keep a regular log or journal from which you can draw material for this statement. Your statement can include essentially anything you find interesting throughout your project, especially insights you may gain from various sources. This statement should be no longer than 5 pages.

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Policies & Procedures

1. Students are expected to take primary responsibility for the development of their capstone projects. You are expected to conceptualize, carry out, and report your projects. I suggest you formulate your project to help you in your academic career (e.g. thesis chapter, published paper, etc.).

2. All paper portions of this project must be done on a computer or word processor.

Use the same word processing program for all your work so that earlier steps of your paper can easily be incorporated into later steps.

3. Pay special attention to how you use source material so as to avoid plagiarism. 4. If you have any questions, please feel free to ask me. I can help with source

material, project ideas, conceptualizations, etc.

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APPENDIX 4


Block II: Biosphere’s Productivity Cycle Fall 2005

LAB 1: RESEARCH ON THE MIND

1. The Scientific Method ………………………………………………………… 1 2. Starting a Research Project ………………………………………….........… 6 3. Reporting Scientific Work ……………………………………………...…….. 8 4. The Oral Presentation ………………………………………..…………..…. 10 5. Group Communications …………………………..…………………...……. 12 1. The Scientific Method

Science is best defined as a careful, disciplined, logical search for knowledge about any and all aspects of the universe, obtained by examination of the best available evidence and always subject to correction and improvement upon discovery of better evidence. What's left is magic. And it doesn't work.

-- James Randi The scientific method helps us create research that is quantifiable (measured in

some fashion), verifiable (others can substantiate our findings), replicable (others can repeat the study), and defensible (provides results that are credible to others--this does not mean others have to agree with the results). The scientific method is often used in everyday life and should be evident in any research report, paper, or published manuscript.

Corollaries among the Scientific Method, Common Sense, and Paper Format

Scientific Model Common Sense Paper Format Research Question Why Intro Develop a theory Your answer Intro Identify variables How Method Identify hypotheses Expectations Method Test the hypotheses Collect/analyze

data Results

Evaluate the results What it means Conclusion Critical review What it doesn’t

mean Conclusion

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Observatio Prediction

not consistent-

modify hypothesis

Hypothesis

Consistent

Theory

TESTS

1.1. Scientific Method: The Steps

The scientific method is the best way yet discovered for winnowing the truth from

lies and delusion. 1. Observe some aspect of the universe. 2. Invent a tentative description, a hypothesis that is consistent with what you

have observed. 3. Use the hypothesis to make predictions. 4. Test those predictions by experiments or further observations and modify the

hypothesis in the light of your results. 5. Repeat steps 3 and 4 until there are no discrepancies between theory and

experiment and/or observation.

When consistency is obtained the hypothesis becomes a theory and provides a coherent set of propositions which explain a class of phenomena. A theory is then a framework within which observations are explained and predictions are made.

Figure 1. Scientific method flow diagram.

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The great advantage of the scientific method is that it is unprejudiced (mostly): you do not have to believe a given researcher; you can redo the experiment and determine whether his/her results are true or false. The conclusions will hold irrespective of the state of mind, or the religious persuasion, or the state of consciousness of the investigator and/or the subject of the investigation. Faith, defined as belief that does not rest on logical proof or material evidence, does not determine whether a scientific theory is adopted or discarded.

Watch out for anecdotes. – Beware of studies or statements that are based on extremely small sample sizes, especially those based on a sample size of 1. For example, if the conclusion of an analysis relies on the statement from one individual, one measurement, or one observation, then be careful with conclusions being drawn. This sort of data may make for interesting stories, but the results alone are NOT scientific, and no conclusions should be based on them. Further work is required. A theory is accepted not based on the prestige or convincing powers of the

proponent, but on the results obtained through observations and/or experiments which anyone can reproduce: the results obtained using the scientific method are repeatable. In fact, most experiments and observations are repeated many times (certain experiments are not repeated independently but are repeated as parts of other experiments). If the original claims are not verified, the origin of such discrepancies is hunted down and exhaustively studied.

In some cases, depending on the nature of the questions, we cannot perform

experiments; all information is obtained from observations and measurements. Theories are then devised by extracting some regularity in the observations and coding this into physical laws.

There is a very important characteristic of a scientific theory or hypothesis which

differentiates it from, for example, an act of faith: a theory must be ``falsifiable.'' This means that there must be some experiment or possible discovery that could prove the theory untrue. For example, Einstein's theory of Relativity made predictions about the results of experiments. These experiments could have produced results that contradicted Einstein, so the theory was (and still is) falsifiable.

In contrast, the theory that ``the moon is populated by little green men who can

read our minds and will hide whenever anyone on Earth looks for them, and will flee into deep space whenever a spacecraft comes near'' is not falsifiable: these green men are designed so that no one can ever see them. On the other hand, the theory that there are no little green men on the moon is scientific: you can disprove it by catching one. Similar arguments apply to abominable snow-persons, UFOs, the Loch Ness Monster, etc.

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A frequent criticism made of the scientific method is that it cannot accommodate anything that has not been proved. The argument then points out that many things thought to be impossible in the past are now everyday realities. This criticism is based on a misinterpretation of the scientific method. When a hypothesis passes the test it is adopted as a theory it correctly explains a range of phenomena it can, at any time, be falsified by new experimental evidence. When exploring a new set or phenomena, scientists do use existing theories but, since this is a new area of investigation, it is always kept in mind that the old theories might fail to explain the new experiments and observations. In this case new hypotheses are devised and tested until a new theory emerges.

1.2. What is the difference between a fact, a theory and a hypothesis?

In popular usage, a theory is just a vague and fuzzy sort of fact and a hypothesis is often used as a fancy synonym to `guess'. But to a scientist a theory is a conceptual framework that explains existing observations and predicts new ones. For instance, suppose you see the Sunrise over the horizon. This is an existing observation which is explained by the theory of gravity proposed by Newton. This theory, in addition to explaining why we see the Sun move across the sky, also explains many other phenomena such as the path followed by the Sun as it moves (as seen from Earth) across the sky, the phases of the Moon, the phases of Venus, the tides, just to mention a few. You can today make a calculation and predict the position of the Sun, the phases of the Moon and Venus, the hour of maximal tide, all 200 years from now. The same theory is used to guide spacecraft all over the Solar System.

A hypothesis is a working assumption or an educated guess. Typically, a

scientist devises a hypothesis and then sees if it stands up to scrutiny by testing it against available data (obtained from previous experiments and observations). If the hypothesis does stand up to scrutiny after repeated testing, it is then considered to be a theory.

1.3. Occam’s Razor?

When a new set of facts requires the creation of a new theory, the process is far from the orderly picture often presented in books. Many hypotheses are proposed, studied, rejected. Researchers discuss their validity (sometimes quite heatedly) proposing experiments which will determine the validity of one or the other, exposing flaws in their least favorite ones, etc. Yet, even when the unfit hypotheses are discarded, several options may remain, in some cases making the exact same predictions, but having very different underlying assumptions. In order to choose among these possible theories a very useful tool is what is called Occam’s razor or the Principle of Parsimony.

Occam’s razor is the principle proposed by William of Occam in the fourteenth

century: ``Pluralitas non est ponenda sine necessitate,'' which translates as ``entities should not be multiplied unnecessarily.''

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In many cases this is interpreted as ``keep it simple'', but in reality the Razor has

a more subtle and interesting meaning. Suppose that you have two competing theories which describe the same system, if these theories have different predictions then it is a relatively simple matter to find which one is better: one does experiments with the required sensitivity and determines which one give the most accurate predictions. For example, in Copernicus' theory of the solar system the planets move in circles around the sun, in Kepler's theory they move in ellipses. By measuring carefully the path of the planets it was determined that they move on ellipses, and Copernicus' theory was then replaced by Kepler's.

But there are theories which have the very same predictions and it is here that

the Razor is useful. Consider form example the following two theories aimed at describing the motions of the planets around the sun:

1. The planets move around the sun in ellipses because there is a force between

any of them and the sun which decreases as the square of the distance. 2. The planets move around the sun in ellipses because there is a force between

any of them and the sun which decreases as the square of the distance. This force is generated by the will of some powerful aliens.

Since the force between the planets and the sun determines the motion of the former and both theories posit the same type of force, the predicted motion of the planets will be identical for both theories. The second theory, however, has additional baggage (the will of the aliens) which is unnecessary for the description of the system.

If one accepts the second theory solely on the basis that it predicts correctly the motion of the planets one has also accepted the existence of aliens whose will affect the behavior of things, despite the fact that the presence or absence of such beings is irrelevant to planetary motion (the only relevant item is the type of force). In this instance Occam’s razor would unequivocally reject the second theory. By rejecting these types of additional irrelevant hypotheses, you are guarding against the use of solid scientific results (such as the prediction of planetary motion) to justify unrelated statements (such as the existence of the aliens), which may have dramatic consequences. In this case the consequence is that the way planets move, the reason we fall to the ground when we trip, etc. is due to some powerful alien intellect, that this intellect permeates our whole solar system, it is with us even now...and from here an infinite number of paranoid derivations.

For all we know the solar system is permeated by an alien intellect, but the motion of the planets, which can be explained by the simple idea that there is a force between them and the sun, provides no evidence of the aliens' presence nor proves their absence.

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When we are face with two theories which have the same predictions and the available data cannot distinguish between them, the Razor directs us to study in depth the simplest of the theories. It does not guarantee that the simplest theory will be correct, it merely establishes priorities.

A related rule, which can be used to slice open conspiracy theories, is Hanlon's

Razor: ``Never attribute to malice that which can be adequately explained by stupidity.''

The objective of science is to explain reality in such a fashion so that others may develop their own conclusions based on the evidence presented. To do this, scientists use the scientific method to as a systematic approach to understanding the world around us that employs specific rules of inquiry. 2. Starting a Research Project

Before starting a research project you should devise a plan to make sure you use your time efficiently. Here are some things you should consider when planning your research:

1. How long do you have to conduct your research?

don't leave it to the last minute - plan your time! do you only have time to consult books and periodicals held in the Library, or

do you have time to order inter-library loans? do you have time to consult several databases for references or just one?

2. How much detail do you need?

if you just need an overview of a topic then an encyclopedia or book might

give you enough information if you are starting a Ph.D. you will need to find all relevant publications

3. Think about your topic

what key words describe it? think about synonyms or other related terms - include them in your search what years do you need to cover? Temporal scale? is your research limited to one country or geographical region? Geographical

scale?

4. Learn how to search databases efficiently using Library guides

consult the ‘Articles Indexes and Databases’ of the UND Chester Fritz Library web page for help on building a search strategy

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experiment with a search strategy with specific databases (e.g. Biological Abstracts)

use the online help screen provided by each database The Chester Fritz Library web site also contains links to many other valuable

references you may find useful. It also holds a number of books which include guidance on planning your research. Also, check out for detailed guidance in formulating a successful search strategy: http://www.lib.berkeley.edu/TeachingLib/Guides/Internet/Strategies.html

5. Develop a research question

The research question should be a clear statement about what you intend to

investigate. It should be specified before research is conducted and openly stated in reporting the results.

Your research question should be relevant and advance the field of study. You can only know this by conducting an extensive literature search and gaining knowledge of the current state of the field. NEVER assume that you know the current state of the field; it’s always changing.

One conventional approach is to put the research question in writing in the introduction of a report starting with the phrase "The purpose of this study is ..." This approach forces the researcher to:

o identify the research objective (allows others to benchmark how well the

study design answers the primary goal of the research) o identify key abstract concepts involved in the research

Research Question: Is the quality of public sector and private sector employees different?

Purpose statement: The purpose of this study is to determine if the quality of public and private sector employees is different.

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Abstract concepts: The starting point for measurement. Abstract concepts are best understood as general ideas in linguistic form that help us describe reality. They range from the simple (hot, long, heavy, fast) to the more difficult (responsive, effective, fair). Abstract concepts should be evident in the research question and/or purpose statement. An example of a research question is given below along with how it might be reflected in a purpose statement. In general, abstract concepts will need to be defined. Always be careful of presenters who rely on abstract concepts to illustrate a point.

6. Develop Hypothesis

A hypothesis is one or more propositions that suggest why an event or phenomenon occurs. It is our view or explanation for how the world works.

Hypotheses provide a framework for further analysis that are developed as a non-normative explanation for "What is" not "What should be."

A hypothesis should have logical integrity and include assumptions that are based on paradigms. These paradigms are the larger frame of contemporary understanding shared by the profession and/or scientific community and are part of the core set of assumptions from which we may be basing our inquiry.

7. Identify Variables

Variables are measurable abstract concepts that help us describe relationships.

In the previous research question "Is the quality of public sector and private sector employees different?" the key abstract concepts are employee quality and employment sector. To measure "quality" we need to identify and develop a measurable representation of employee quality. Possible quality variables could be performance on a standardized intelligence test, attendance, performance evaluations, etc. The variable for employment sector seems to be fairly self-evident, but a good researcher must be very clear on how they define and measure the concepts of public and private sector employment.

8. Many more specific steps… 3. Reporting Scientific Work

Science is a communal activity. Only as the entire community of interested scientists takes up new facts and hypotheses do these facts and hypotheses become part of science. Therefore, one of the major responsibilities of scientists is to see that their work is reported to all those who might be interested. Often this is done by word of mouth when scientists of similar interests gather together at meetings. But to be assured of a permanent place in the scientific edifice, the work is reported in a paper submitted to a scientific journal. In most cases, the paper will not be accepted for

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publication until several knowledgeable scientists from other laboratories who serve as referees have approved it. Often they will suggest editorial changes in the paper or even additional experiments that should be done before the paper is accepted for publication. Papers in science usually follow a standard plan. The paper is divided into several sections as follows.

3.1. Introduction.

This section of the paper describes the scientific question or problem that was the subject of the investigation. The introduction also includes references to earlier reports of these and other scientists that have served as the foundation for the present work. 3.2. Materials and Methods.

Here are precisely described the materials used (e.g., strains of organism, source of the reagents) and all the methods followed. The goal of this section is to give all the details necessary for workers in other laboratories to be able to repeat the experiments exactly. When many complex procedures are involved, it is acceptable to refer to earlier papers describing these methods in greater detail.

3.3. Results.

Here the authors report what happened in their experiments. This report is usually supplemented with graphs, tables, and photographs.

3.4. Discussion.

Here the authors point out what they think is the significance of their findings. This is the place to show that the results are compatible with certain hypotheses and less compatible, or even incompatible, with others. If the results contradict the results of similar experiments in other laboratories, the discrepancies are noted here, and an attempt may be made to reconcile the differences.

3.5. Acknowledgments.

In this brief but important section, the authors give credit to those who have assisted them in the work. This usually includes technicians (who may have actually performed most of the experiments!) and other scientists who donated materials for the experiments and/or gave advice about them.

3.6. References.

This section gives a careful listing of all earlier scientific work referred to in the main body of the paper. Most of the references are to other scientific papers. Each reference should provide enough information so that another person can locate the

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document. This means that each reference should include the name(s) of the author(s), the journal or book in which the report appears, and the year of publication. In the case of scientific journals, the volume number in which the paper appears and the page number on which the paper begins should be included. Sometimes the full title is given as well, although scientific papers often have such long titles that this is omitted from the reference.

3.7. Summary or abstract.

This section includes only the essence of the other sections. It should be as brief as possible, telling the reader what the goal of the experiment was, what was found, and the significance of the findings. The abstract is often placed at the beginning of the paper rather than at its end.

When a paper is written and rewritten and every coauthor has reviewed and

revised it, you will reach a point where you just cannot see how to make it better. You have now reached the point where you ask for reviews from peers. These might be the most valuable types of reviews because your peers probably have a cursory and not an in-depth knowledge of your work. They will probably make suggestions about issues you have not thought of, or provide insight to issues you may have passed over. Once this is done and additional changes are made, you will probably be ready to submit the paper for publication (or grade).

Submitting a paper to a scientific journal requires that you first read the

“Instructions to Authors.” This information will probably tell you about page charges and submission requirements for page size, line spacing, and numbering, and other style issues. It is important to submit your paper to only one journal. You may think your chances for acceptance are better if you submit your paper to more than one journal. This is typically not allowed and considered unethical. Acceptance of your paper depends on not only how good the research and how well it is written, but also on the suitability of the subject and the acceptance rate of the journal.

4. The Oral Presentation

Nothing is worse for an audience member than to be forced to sit through a presentation that is poorly prepared and inadequately presented. Below is an outline of questions you should consider when preparing and presenting your presentation.

4.1 The Presentation

A. Introduction

1. Are your hypothesis and objectives clear for the audience? 2. Do you provide the audience with clear rationale and justification for

your study?

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3. Does your introduction follow a logical pattern, and is it related to other literature and scientific principles?

B. Materials and methods

1. Do your methods have the support of the literature and scientific principles?

2. Do you show a logical, systematic process for executing the experiment and collecting the data to carry out your objectives?

3. Do you make clear your use of appropriate experimental design and statistical analyses?

C. Results and discussion

1. Do you summarize results (i.e. emphasize main points, as you begin and end this section)?

2. Do you relate the results clearly to your objectives? 3. Do you carefully choose a limited number of data points to support

your contentions and present them in simple illustrations, graphs, tables, and lists?

4. Do you discuss your points in terms of: a. Their relation to other research. b. Their practical or scientific applications?

D. Conclusions 1. Do the conclusions reiterate main points for the audience to

remember? 2. Do you show a list and clearly relate it to your objectives? 3. Do you give examples of application and use for your findings?

4.2 Visual aids

A. Number – Are there too many or too few slides for the time you have? B. Content

1. Are the slides clearly coordinated with your presentation? 2. Is the purpose of each slide readily apparent? 3. Do you have a balance of data, lists, and information slides with

photographs interspersed throughout? 4. Have you included all expected slides: title, list of objectives, and

conclusions?

C. Quality – Are your slides: 1. Neat and spaced to fill the screen? 2. Simple and free from excessive data? 3. Easy to comprehend (e.g. proper size print, good content, good

design, clearly labeled axes)?

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4. Free from garish color or any other embellishment that could distract from your message?

4.3 Speaker

A. Are you prepared? 1. Are you familiar with your speech and slides? 2. Will you and your audience be comfortable with your appearance?

B. To what extent do the following support or distract: 1. Mannerisms and gestures? 2. Audience contact (eye contact, and facial expressions)? 3. Voice, speech patterns, and ease in speaking? 4. Your attire, posture, and poise?

C. During your presentation, keep the following in mind: 1. Avoid reading from the slides or from notes. 2. Be sure your eye contact covers all the audience. 3. Put the pointer down when you’re not using it. This may not be

possible in all cases. 4. Don’t put your hands in your pockets. 5. Never apologize or make an excuse for a bad slide. A bad slide is

worse than no slide. 6. Keep your voice enthusiastic and loud enough. 7. Be sure to use enough but not too much time.

5. Group Communications

Group communications are quickly becoming the status quo in educational, private industry, and research settings. As with individual efforts, preparation and competent execution are important to provide clear communication and prevent wasted time and effort. Selecting a format was well as preparing for and carrying out communication with a group depends to a large extent on whether and audience is involved.

5.1 Decision Making

Decision-making involves alternatives. Defining what the alternatives will likely require research and discussion. Making the best possible decision can depend on gathering information and even solving problem along the way. But after discussion, the group should reach a consensus or conduct a vote to make a final decision.

5.2 Problem Solving

Example problem solving procedure:

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A. The problem is clearly defined and objectives are set out and understood

by all members of the group. B. Members of the group plan their individual and collective actions. They

may divide responsibilities for gathering information and offering opinions. C. As individuals and as a group, they devise a plan of action. D. They act on the plan and analyze outcomes. E. They evaluate the results if their actions and determine whether the

solution was acceptable.

Additional web references: http://methods.fullerton.edu/framesindex.html THIS WEEK’S LAB ASSIGNMENT: Questions (1 pt. each): 1) Science is:

(a) absolute, (b) mystical, (c) testable, (d) unpredictable

2) Scientific results must be verified by: (a) constructing plausible theories, (b) consulting noted scientific authorities, (c) experiments, (d) government agencies

3) A hypothesis is: (a) a guess based on observations, (b) a process of experimentation, (c) an Italian building, (d) the truth

4) What would scientists do to test a hypothesis? (a) ask questions, (b) create an experiment, (c) make observations, (d) none of the above

Longer questions (8 pts. each): 5) Cold Fusion. It was touted as the answer to the world's energy problems: A pair

of researchers from the University of Utah announced in 1989 that they had achieved fusion with a simple apparatus at room temperature. Fusion is the joining of two nuclei to form a larger nucleus. If unstable, the nucleus will break apart and release energy. The generally acceptable methods of fusion involve extremely high temperatures or particle accelerators--dangerous and expensive

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methods. The discovery of a reliable cold fusion method had the potential of supplying cheap energy to the world. If you were asked about the validity of cold fusion, what would you say?

6) The Roswell Crash. Is Agent Mulder right? Are there Men In Black? Did a UFO

crash in Roswell, N.M., in 1947? A good proportion of people think the latter happened – according to a 1997 Gallup poll, 80% of Americans have heard of the Roswell incident and 31% believe it's true. In 1947 a rancher found debris which he thought could be from a flying saucer. After a few days of investigation, it was declared to be from weather balloons and for several decades the incident was closed. About 30 years later a UFO researcher started interviewing hundreds of "witnesses" to the crash – witnesses who for some reason kept quiet for 3 decades, who occasionally changed their stories, and sometimes told outright lies. Rumors of a government cover-up and alien bodies abounded, including a Fox-TV special Alien Autopsy. As circumstances sometimes have it, you are asked about the scientific validity of the Roswell Crash. How do you respond?

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APPENDIX 5



LAB 3: GLOBAL TEMPERATURE CHANGE 1. Introduction10

An overall increase in global-mean atmospheric temperatures is predicted to occur in response to human-induced increases in atmospheric concentrations of heat-trapping ''greenhouse gases”. The most prominent of these gases, carbon dioxide, has increased in concentration by over 30% during the past 200 years, and is expected to continue to increase well into the future. Other changes in atmospheric composition complicate the picture. In particular, increases in the number of small particles (called aerosols) in the atmosphere regionally offset and mask the greenhouse effect, and stratospheric ozone depletion contributes to cooling of the upper troposphere and stratosphere.

Source: Source: http://www.giss.nasa.gov/

Many in the scientific community believe that a distinctive greenhouse-warming

signature is evident in surface temperature data for the past few decades. Some, however, are puzzled by the fact that satellite temperature measurements indicate little, if any, warming of the lower to mid-troposphere (the layer extending from the surface up to about 8 km) since such satellite observations first became operational in 1979. The satellite measurements appear to be substantiated by independent trend estimates for this period based on radiosonde data. Some have interpreted this apparent 10 Modified from Reconciling Observations of Global Temperature Change, 2000, Commission on Geosciences, Environment and Resources, National Academy of Sciences, USA

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discrepancy between surface and upper air observations as casting doubt on the overall reliability of the surface temperature record, whereas others have concluded that the satellite data (or the algorithms that are being used to convert them into temperatures) must be erroneous. It is also conceivable that temperatures at the earth's surface and aloft have not tracked each other perfectly because they have responded differently to natural and/or human-induced climate forcing during this particular 20-year period. Whether these differing temperature trends can be reconciled has an implication for assessing how much the earth has warmed during the past few decades and for potential future temperature trends.

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In this lab, you will explore potential global temperature change across different continents and time periods, and also look at methane and carbon dioxide in the atmosphere. You will initially work alone, but then share your data with the others in the class in order to complete the assignment.

LAB ASSIGNMENT Part 1. Temperature Data Preparation

Temperature records for various weather stations around the world are available

from the NASA Goddard Institute for Space Studies (GISS) (http://www.giss.nasa.gov/data/update/gistemp/station_data/). Each student will select an area to analyze according to the following table.

Name Your Area To Examine Africa Asia Europe North America South America Australia

Go to the website listed above and choose which part of the continent you will

explore. Click that spot on the NASA GISS Surface Temperature website. This should bring up a list of localities with temperature records. Select a locality from this list. Make sure that your site has a reasonably long and continuous record of measurement. Once you have a site selected, click on the “Click for monthly data in table form.” From this raw data, save this page on your hard drive as a text file (not as a webpage). Do not forget where you saved your file and what you called it.

Using Excel, open the saved text file. You will be prompted for information on

how to import this file. You should select: Original Data Type-Delimited; Delimiters-Tab and Space; and Column Data Format-General. After selecting these options, click finish to have your data page. Save this page as an Excel file. Again, do not forget where you saved your file and what you called it. In your data, gaps in the data are registered as “999.9.” If you leave these as they are, your analyses will be highly skewed. Therefore, remove these numbers from the spreadsheet, leaving only blank cells.

Now, compare January, April, July, and October temperature (scatter plots). If

you are not sure how to do this, refer to last week’s lab for specific instructions. Next, use the Insert a linear “trend line” and report the equation and r2 value by checking those boxes in the option menu for trend lines of each scatter plot in your lab report.

Part 2. Greenhouse Gases and the Temperature Record

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From your data above, produce a graph that shows annual temperature average by year (scatter plot with connecting line). Add a trendline and report the equation and r2 value and include in your report. Next, you will add CO2 and CH4 data to your current spreadsheet. To do this, go to Public Drive/ESSP_Public/Biogeochemical Block/Lab-Temperature Change…/ch4.xls (for methane data) and co2.xls (for CO2 data). Open each of these files and select those cells of TOTAL CH4 that correspond to the earliest year of temperature record from your site. For example, CH4 data begins with 1860, but your temperature record may begin in 1945. Select the CH4 cells between 1945 and the last year of temperature data. Copy these cells and paste them in the appropriate place (i.e. corresponds to the correct sequence of years) in your temperature data sheet. Do the same for the CO2 data.

Now, produce a graph that shows annual temperature average by year for your

site and CH4 and CO2. Refer to last week’s lab for hints on how to do this if you are not sure. Add a trend line to each of the variables and include with your report.

Assignment Write a short essay (≤2 pages) describing the changes in temperature at your site noting the magnitude of the change, variations over time, and what consistency, if any, was observed between localities. Address what role, if any, CO2 and/or CH4 may play in any observed temperature change. Be sure to address:

How large was the change in temperature at your site and how consistent was it from month to month?

How consistent were the changes observed among other localities? Do you think the temperature trends you observe in your data reflect a significant

change in climate over time? Why or why not? What role, if any, do CO2 and/or CH4 play in any observed temperature change?

Grading will be based on the following criteria: spelling and grammar (2 pts.), logical argument and clarity (10 pts.), structure and flow of writing (3 pts.), proper formatting and inclusion of graphs (10 pts.).

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APPENDIX 6



Select an environmental-related text to examine. This may be a brochure, flyer, advertisement, advisory, newspaper or magazine article, etc. You will provide a written paper and lead a class discussion that examines the following:

What message(s) is the text attempting to communicate? Can you identify the intent of the text? Who or what is the target audience of the text?

Using the Jacobson model of communication, what assumptions is the sender

making about the receiver?

What messages (if any) does it communicate about nature or ecosystems?

What techniques or strategies does it use?

In your estimation, how effective is it?

Include anything else you find interesting to discuss. Make references to class readings as appropriate.

The written portion of this assignment should not exceed five pages of text (or 10 pages with pictures, figures, etc.). The discussion portion should be targeted to about 30 minutes.

This assignment will be due on September 6th. Your presentation will also be on

that day.

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APPENDIX 7



LAB 3: PREDICTIVE SPATIAL MODELING OF SPECIES’ DISTRIBUTIONS 1. Introduction

New computational and GIS technologies provide innovative opportunities to use species locality data to create predictive spatial models and maps of species distributions. One technique of considerable interest, ecological niche modeling, uses primary locality data to discover the association between a species’ geographical occurrence and the environmental dimensions that may determine its geographic distribution. This approach produces an approximation of a species’ fundamental ecological niche, which provides a basis for understanding numerous ecological and geographic phenomena related to its distribution. This approach also produces a model for predicting what a species’ geographical distribution might become, avoids numerous problems associated with sampling bias, and has excellent overall predictive abilities. One way it avoids sampling bias is by identifying a species’ ecological niche without a complete or balanced sample of the species’ geographic distribution.

2. Ecological Niche Modeling

We will use the Genetic Algorithm for Rule-Set Prediction (GARP)11, an iterative, artificial intelligence approach that includes several distinct algorithms (e.g. BIOCLIM, logistic regression). GARP is a software package for biodiversity and ecological research that allows the user to predict and analyze wild species distributions. GARP is a genetic algorithm that creates ecological niche models for species. The models describe environmental conditions (abiotic primarily) under which the species should be able to maintain populations.

For input, GARP uses a set of point localities where the species is known to

occur and a set of geographic layers representing the environmental parameters that might limit the species' capabilities to survive. GARP searches iteratively for non-random correlations between species presence and absence and environmental parameter values using several different types of rules. Each rule type implements a different method for building species prediction models. Currently there are four types of rules implemented: atomic, logistic regression, bioclimatic envelope, and negated bioclimatic envelope rules. For a comprehensive description of GARP algorithm, please

11 Desktop GARP 1.1.3. http://www.lifemapper.org/desktopgarp/

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read the GARP Technical Manual and Users Guide (http://biodi.sdsc.edu/Doc/GARP/Manual/manual.html). 3. Getting Started 3.1. The GARP Interface The GARP user interface is relatively simple. It contains just one window where the user specifies all the parameters and data to be used in the experiment. Below is a sample of the interface.

Below is a detailed functional description of each user interface panel. The Species Data Points panel handles the species occurrence (point) data. A sample of this area is shown below.

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New species occurrence information can be entered by clicking the Upload Data Points button. It will open a dialog box to specify the location of the occurence data file. Currently three formats are supported: Comma delimited, MS Excel Spreadsheets and ArcView Shapefiles.

Comma delimited and Excel files should contain three columns: the first one for species name, the second for longitude, and the third for latitude. The first line is ignored, so it can be used for labels.

In this version, GARP accepts only files in this format, so make sure the columns

are ordered: species name, longitude and latitude. Notice that longitude comes before latitude.

Each line of the file represents a single data point entry for the species. Data

points for the same species must come together. Different species names define different species for the software. Below is a sample Excel worksheet and the corresponding comma delimited file containing species information for two species. The actual files can be downloaded at MS Excel sample and comma delimited sample.

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3.2. Optimization Parameters

On the Optimization Parameters panel, the user can specify some parameters that control the overall behavior of the genetic algorithm. A sample of this panel is shown below.

The number of runs per experiment defines how many times each distinct task will be performed within the experiment. For example, for two species and 10 runs per

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experiment, 20 runs in that experiment will be executed: 10 for the first species and 10 for the second one.

The convergence limit establishes a stop condition for iterations within the genetic algorithm. Its behavior varies depending on how difficult or easy the problem is. Usual values are between 0.01 and 0.10. If this parameter is set to 0, the algorithm will stop only when the maximum number of iterations is reached.

Max iterations value establishes another stop condition for the genetic algorithm. It forces the optimization to stop at the specified iteration, even if the convergence limit has not been reached yet. More iterations tend to yield more stable results. Usual values are between 100 and 1000.

The rule type checkboxes allow the user to specify which algorithm is used to

produce rules in the species model. For this assignment, you will use all of the rules. The all combinations checkbox generates one task for each combination of the

checked rules. For example, if range, logit and atomic rules are checked, GARP will create tasks where only each of those rules are used, then one for range and logit rules, one for range and atomic rules, one for logit and atomic rules, and one for all three rules combined. This is useful for analyzing the impact of each particular rule on the results. The labels below the checkbox show how many combinations will be created and also the total tasks or runs that will be executed (combinations times runs).

Unless otherwise stated, you will use the default settings in the Optimization

Parameters section of GARP.

3.3. Environmental Parameters

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The Environmental Layers panel allow the user to define the environmental coverages that will be used as input for the prediction. The algorithm will try to correlate the input data points to the values on those layers to get the final prediction. The dataset combo box displays the choices for the dataset that will be used on the experiment. The datasets listed on this combo box are the ones scanned using the menu option Datasets->Scan directory.... Once the dataset has been chosen, GARP will automatically list all layers present on that dataset on the layers to be used list box. There, the user can control which layers will be used by clicking on the checkbox that appears to the left of each layer name.

Below the layers list, there are three radio buttons that define how the selected

layers will be used. The first one, all selected layers, will force GARP to use all selected layers in the optimization. All combinations of selected layers will cause the experiment to have one task for each possible combination of the selected layers. The all combinations of selected size N radio button has similar effect, but will limit the experiment to the combinations that contains exactly N layers. The last two alternatives using combinations of layers are useful for determining which layers are important to a species. A method for analyzing that would be using linear multiple regression to predict the error values (omission and commission), using the information on whether a particular layer was used on a task as an independent variable.

Note: The use of combinations of layers may cause the number of tasks within

the experiment to be too large. There is a label next to the bottom of the panel that shows how many combinations that setup will yield. Tests have shown that GARP can handle well up to 10,000 tasks in the same experiment. 3.4. Output Parameters

The Output panel specifies the output prediction map format and the output directory for maps and other generated documents.

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The prediction maps can be generated in three formats:

• bitmaps: MS Windows bitmaps, with extension ".bmp"; • ASCII raster grids: ASCII text format, with extension ".asc"; • ESRI Arc/Info grids: ESRI proprietary format for grid spatial data storage and

management. A separate directory is created for each grid.

Another important file that is stored on the output directory is the file result.xls which stores a summary of all tasks, error messages, result parameters, statistical tests, accuracy, and more.

All .bmp, .asc and other result files are stored under the directory specified on the

text field Output directory. This must be a valid folder (local or remote) accessible through the computer being used. ESRI Arc/Info grids are stored in subdirectories of the Output directory and called sequentially grid00000, grid00100, grid00200 and so on. The directory grid00100 for example, stores all grids resulting from tasks 100 through 199. This is because of an ESRI limitation on the number of grids allowed in a directory.

3.5. Visualizing Results

Import each grid into ArcMap to visualize. I will provide detailed methodology how to do this during the lab. Please be prepared to take notes.

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LAB ASSIGNMENT In this lab, you will use GARP to produce predictive geographical maps of species’ distributions over landscapes. Specifically, you are to do: (1) Produce four predictive distributional map for two species. The locality data for

these species will be provided to you. For each species, I want a world-wide analysis and a North American analysis using the “Best Subsets” setting. Print these maps out keeping in mind last week’s Lab and qualities of good maps. (14 pts.).

(2) Produce a map at the continental scale not using the “Best Subset” option. You will

use the same data from #1; you choose the species. Print out and provide a brief explanation as why these two differ. (3 pts.)

(3) Provide three uses that maps produced using GARP might be used for (e.g.

identifying areas that should be conserved). (3 pts.). Further Readings Anderson, R. P., D. Lew, and A. T. Peterson. 2003. Evaluating predictive models of

species' distributions: criteria for selecting optimal models. Ecological Modelling 162: 211-232.

Peterson, A. T., J. Soberón, and V. Sánchez-Cordero. 1999. Conservatism of

ecological niches in evolutionary time. Science 285: 1265-1267. Peterson, A. T., M. A. Ortega-Huerta, J. Bartley, V. Sánchez-Cordero, J. Soberón, R. H.

Buddemeier, and D. R. B. Stockwell. 2002. Future projections for Mexican faunas under global climate change scenarios. Nature 416: 626-629.

Sánchez-Cordero, V., and E. Martinez-Meyer. 2000. Museum specimen data predict

crop damage by tropical rodents. Proceedings of the National Academy of Sciences USA 97: 7074-7077.

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APPENDIX 8


Block II: Biogeochemical Cycle Spring 2005

Micro-Economics of Bottled Water Simple Homework: 1) Use the daily water use data determined on Wednesday along with GF price info and determine what your daily average water use costs on average. 2) Figure out how many 8 oz. glasses of tap water you could have for the price of a Clifford Hall vending machine bottle of 12 oz. Desani (Coca-cola) water. Hard Homework: 3) Thinking about your answer to Q2, justify, in purely economic terms, why you would ever buy bottled water (think about all the reasons you buy bottled water as well as why others might) – if you have honestly never purchased bottled water, than (if you want) explain why.

4) Describe, in as many ways as you can, how this issue of bottled water is linked with the other cycles covered in 501 & 502 (no more than two pages).

This is funny because it essentially depicts what Coca-cola does to produce Desani the nations # 1 bottled water product.

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APPENDIX 9 Department of Earth System Science and Policy ESSP 502, Spring 2005 502 Block I: Material Cycling Full Cost Accounting Analysis of hypothetical landfill

Landfills have many types of “impacts”, including biophysical impacts such as contamination of groundwater and socio-economic impacts such as those on property values or potential health risks. The first problem we encounter is therefore how to decide which potential impacts to include in an analysis and which to exclude. Many analyses of the “costs” of landfilling consider only the obvious, direct costs, such as land purchase, construction costs, and supplies and labor for operation and management. It can be argued that such an approach significantly underestimates the true costs of a landfill project. We know that landfills have the potential to create serious impacts on the built and natural environment, and on people who are part of those environments. Yet these impacts are almost always excluded from, for instance, a cost benefit analysis of waste management alternatives.

Today’s assignment is to perform a Full Cost Accounting Assessment of a hypothetical landfill project.

Using the data provided below in Tables 1-3 found on page 3, your task is to calculate a “truer”(more complete) cost of this hypothetical landfill project.

Calculating the true costs of a landfill project demands the use of several different tools. The simple approach is to break the task into several steps.

1) Calculate the capital costs 2) Calculate the operating costs 3) Calculate the potential “opportunity costs” of the land 4) Calculate the costs of close-out 5) Calculate the costs of property-value impacts 6) Estimate the costs of other environmental impacts

Below is a little step-by-step process you are required to follow (HINT – it will be useful to create a cash flow table which includes: cost item, cost, timing, discounting formula) 1) Calculate the capital costs

The first and perhaps the simplest task is to calculate the costs of building the landfill. This step comprises several discrete calculations:

1) Calculate the total volume of the landfill. 2) Calculate the portion of that volume that is usable for waste disposal (as

compared to soil cover) = the volume of waste that the landfill can receive. 3) Calculate the mass of waste that the landfill can receive, from the known volume

and estimated waste density. 4) Calculate the costs of buying the land for the site.

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5) Calculate the costs of excavation. 6) Calculate the cost of a liner system, which will comprise four layers: a clay liner,

a synthetic liner, a geo-textile layer, and a drainage net. Use unit costs and known landfill volume.

7) Add the costs of a lift station and a leachate collection and treatment system. 8) Total these costs.

2) Calculate the operating costs Operation and maintenance costs are typically much lower and less variable than one-time costs like construction. Assuming that the costs of hauling wastes are common to any waste disposal option, we can omit them from further consideration. Other operating costs can be calculated as follows:

1) Calculate the costs of covering waste with soil. 2) Calculate the volume of leachate generated (rainfall/yr*area*proportion of rainfall

that yields leachate). 3) Calculate the costs of leachate treatment. 4) Calculate the costs of generating gases from the landfill. In this case the city

proposes to construct gas collection equipment as part of the landfill design, so there is no additional cost related to gas generation.

5) Calculate the costs of any labor required (assume filling and treatment costs are included in the unit costs given). To simplify, ignore management costs.

3) Calculate the potential “opportunity costs” of the land Assume that the land base in this example is productive agricultural land. How would you figure out the agricultural opportunity cost? What is an appropriate time scale? 4) Calculate the costs of close-out The costs of close-out, or decommissioning, are hard to estimate with accuracy, simply because we cannot guess what environmental or regulatory conditions may prevail when the landfill is full. An estimate of 5% of total capital (construction) costs is not unrealistic for site closure. Another 2% or so of construction costs should likely be allocated for ongoing site management and monitoring after closure. – These costs could go on indefinitely – you decide. 5) Calculate the costs of property-value impacts Once the routine costs of construction and operation have been calculated, it should be possible to move onto less traditional cost areas. Among these, and often foremost in the minds of site neighbors, are property value impacts. We can never estimate these costs with certainty, but we can work from empirical evidence available in the literature, such as those produced by Hirshfeld et al., (1992). We would simply calculate the number of neighboring homes, their distance from the site, and the

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probable depreciation in their property values, and sum those costs. - - Are these onetime costs? You decide. Table 1. Basic Assumptions, proposed landfill project. Total land area available 304 ha Fill area 81 ha Average Depth of fill 15 meters Depth of clay liner 0.6 m Volume of cover 20% of total volume In-place refuse density 590 kg/cubic meter Land cost

Potential Opportunity Costs Agricultural rent

$24,700/ha $247/ha

Excavation cost $6,175/ha Cost of routine landfill cover $6,175/ha Average annual rainfall 102 cm Leachate/precip ratio 0.4 Rate of filling 682 t/day Estimated landfill life span ? – you tell me. Period of public ownership following close-out 60 years Rate of land appreciation 4% annually Annual property tax rate $1.50/$100 assessed value Typical value of residences within 5k of site $70,000 Source: Hirshfeld et al., 1992 Table 2. Estimated unit costs for key project components. Clay liner $5.23/ m3 Synthetic liner $0.11/mil-square meter Geotextile $0.16/ m2 Drainage net $0.27/ m2 Lift (pumping) station $30,000 each On-site pretreatment Construction Operation

$150,000 $0.001/ liter

Leachate hauling and treatment $0.008/ liter Source: Hirshfeld et al., 1992 Distribution of residences around the site It is possible to estimate the number of homes located within 0.5 km, within 0.5 to 1 km, and within 1 to 5 m. Their distribution is approximately as follows: Table 3. Distribution of residences around proposed landfill site Distance from site boundary (km)

Relative location Within 0.5 0.5 to 1 1 to 5 West 99 55 1 South 17 12 15 East 54 127 83

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North 5 6 46 Total 175 200 145 Source: Hirshfeld et al., 1992 Property values are known to depreciate more quickly closer to a landfill site. Work by Hirshfeld et al. (1992) suggests that $70,000 homes within 0.5 km of a landfill depreciate on average about $18,000 after the landfill is sited; those between 0.5 to 1 km from the site depreciate by about $15,000; and those between 1 and 5 km depreciate by about $7,000. Below is a discounting decision tree that may be useful in calculating some of the costs. Discounting Formula

Source: Klemperer, W.D. 1996. Forest Resource Economics and Finance. McGraw-Hill Series in Forest Resources. Mcgraw-Hill Inc. 552 p. Estimate (in this assignment “Qualify”) the costs of other environmental impacts The “costs” of other environmental impacts are very difficult to estimate, and will likely be subject to considerable public debate. This, however, doesn’t mean that such estimates are not worth preparing or including in an analysis. Rather, it means that the

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analyst must make very clear what assumptions underlie the analysis and the methods used to estimate “costs”.

Identify the probable impacts

People identify environmental impacts in different ways - this , in fact is the crux of the debate on environmental impact assessment. Some common approaches include subjective assessment (in which the analyst simply lists the impacts that he or she believes are important: a risky process because it inherently reflects the interests and biases of the analyst); and matrix analysis, in which the analyst uses one of several types of matrix to organize information about project activities and their impacts. While matrix analysis is still very subjective, it is often more comprehensive than simply “eyeballing” a situation. Its clear organization can also assist the analyst in seeking additional viewpoints from external stakeholders. The most common form of an environmental impact assessment matrix is one like the following example, where project activities are listed down the vertical axis and environmental components are listed across the horizontal axis. The resulting matrix can be filled with information about the direction and magnitude of expected impacts. Even though this analysis is necessarily general and simplified, if completed for a detailed list of probable areas and severity of impact. NOTE: This type of study is what leads to more comprehensive (and less subjective) economic assessments of individual components. Many of you were introduced to techniques used in non-market valuation of environmental goods and services (and losses thereof due to damage) such as contingent valuation. For this assignment we will leave the quantification for another day, instead we will deal only with the qualification of potential values.

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For this assignment create a matrix similar to the one above (you may change its format if you wish – that is add whatever dimensions you think should be there). Key point: In this case use the location of Manvel, ND to guide your assessments and assumptions. Fill in the “direction” of impact. If you wish you may put in an estimated magnitude on either a 10 point scale or a 0 to 1 scale. Precision such as that given in the example is not required – though if you’re interested in knowing how such precision can be estimated, the likely technique is called a Delphi analysis and I would be more than happy to explain it to you. Final Analysis: When you have determined the capital costs, the long-term operating and maintenance costs, and some examples of socio-economic costs (e.g. real estate depreciation, opportunity costs): Sum all costs and express on a per tonne basis as follows: Tipping Fee* ________/tonne Leachate, gas and monitoring costs ________/tonne Property depreciation ________/tonne Opportunity Costs ________/tonne Total “cost” ________/tonne

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*Tipping fee: the fee charged to a landfill user for the disposal of a quantity of solid waste. The tipping fee is intended to reflect the costs of land purchase, construction costs, operation and maintenance, and close-out. This is typically considered the “cost” of a landfill. Questions:

1) What are the observed implications of your final Total “cost” figure above? 2) What costs are still not accounted for in this analysis? How might these costs

impact the total “cost”? 3) What you have done today is only half (the C) of a B/C analysis. What might be

factored into a calculation of the B? 4) What are three take home messages from this exercise?

Sources of information:

Much of this assignment came from ideas and text presented in: Heathcote, I.W. 1997. Environmental Problem Solving: a case study approach. McGraw-Hill Company, NY,NY. 197p.

Data provided by: Hirshfeld, S., P.A. Vesilind, and E.I. Pas.1992. Assessing the true cost of landfills. Waste Management and Research. 10(6): 471-484.

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APPENDIX 10

Department of Earth System Science & Policy ESSP 501

Biosphere Productivity Cycle Student Debate Position: Fall 2005

Stewardship as the Last Best Hope for Biodiversity

According to the latest estimates, the extinction rate has accelerated during the past 100 years to about 1,000 times what it was before human civilization developed. It is further estimated that between 1 and 10 percent of all species are extinguished every decade; about 27,000 species a year. Various attempts at slowing or stopping this mass extinction have mostly met with failure. While scientists universally agree that extinction rates are too high and something must be done, convincing policy makers has been far more illusive. In developing countries, for example, where most biodiversity is found, the economic pressures on are so great, people tend to use whatever resources are available making preservation of biodiversity a perceived luxury that generally cannot be afforded.

Environmentalists, on the other hand, have used various arguments to assign

economic value to biodiversity in the attempt to preserve it. These arguments range from identification of the ecosystem services that biodiversity provides to the role it plays as a hedge against disease and famine. Unfortunately, these arguments have not yet convinced policy makers around the world that biodiversity should be preserved for economic reasons. Because scientists know so little of Earth’s biodiversity, let alone what roles species play in the ecosystems they inhabit, it is likely that economics alone will not slow or stop the current mass extinction. A moral argument for the preservation of Earth’s biodiversity may be the last best hope.

Position (Pro side) Stewardship policies that protect biodiversity are the best and probably only option in slowing or stopping the current mass extinction.

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APPENDIX 11


Block I: Materials Cycle Spring 2005

February 7, 2005 Hi all, I would like to give you some feedback on the Full Cost Accounting assignment involving Solid Waste Management and the issue of landfilling waste. First let me tell you what my a priori learning objectives were for this assignment. The full cost accounting assignment, by using solid waste management issues as the platform for discussion, was meant to serve as an example of and brief introduction to the concept of materials cycling. If the ex-post results (in other words what you actually got out of this activity) were significantly different please let me know! Learning Objectives:

1) To examine how materials can cycle through different dimensions. Using solid waste as the example we briefly explored how waste cycles through a socio-environmental complex and the difficulties in examining the multi-dimensional nature (social, environmental, physical, temporal…) of waste within the Life Cycle of a “thing”.

2) To explore the issue of solid waste management by using a method of social accounting called Full Cost Accounting (FCA).

3) To briefly explore how a method such as FCA might fit into the broader economic concepts found in Benefit/Cost analysis.

4) To explore the possible integration of environmental values into a social accounting process – a process that might be called a socio-environmental or socio-ecological analysis.

5) To introduce you to a simple Environmental Impact Matrix Analysis framework – a process that helps organize a more holistic examination and a process that serves as the precursor to a more advanced socio-economic analysis of the issues at hand.

6) To give you an opportunity to examine, organize and use different types of “data” to reach learned conclusions.

Feedback: With regards to the notion of “feedback” there are two main types that educators can provide: summative and formative. Summative feedback is, as the word suggests, a summation of scores. In other words your grade in a quantitative format – a feedback point that typically comes at the end of something, an assignment or a class for example. Formative feedback on the other hand is

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more qualitative in nature and is designed to evaluate the “process” of learning and is often used to guide and make adjustments while “in stream” so to speak.

1) In summative terms all six of you have scored full points.

2) In formative terms, I was impressed by a number of things:

a. This was not an easy assignment by any means. The “busy-work” parts of the assignment were not difficult, but in the aggregate I though all of you contributed during the discussions and helped make this an interesting exploration of the multi-dimensionality of this topic. You were capable of “reading between the lines” without any prompting.

b. Despite the data imitations I inadvertently built into the assignment, you were able to make appropriate simplifying assumptions and even make “above and beyond” assumptions that allowed the accounting to be more realistic.

c. All of you contributed in important individual ways as well. Some of you brought into the discussion the oft-neglected philosophical aspects of this topic; some contributed computational prowess; some contributed a tenacity that quickly identified gaps in the data; all contributed components of their personal background to the overall discussion.

d. Kandi and Raj should be commended as they accepted additional work in getting up to speed regarding B/C concepts.

3) Also in formative terms, I was a little disappointed that the final Matrix discussion was dictated a little bit more than it should have been by a desire to be “done” with the assignment. I thought the final matrix – though it generated excellent discussion – was a bit limited (i.e. I though some of your assumptions regarding your directional assessment, particularly the D = depends and ND = no decision, should have been articulated to some degree.)

So far, I am pleased with the process that I am observing.

The final due date is Wednesday the 9th – let me know if this causes any problems!

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APPENDIX 12



Capstone Project




Final Paper:


You must include the following in your paper: 1. A review of the background issues, including a statement of need. 2. A discussion of the objectives of your project with a clear rationale for choosing

these objectives. 3. A clear statement and rationale for your choice of target audience(s). Why these

folks? 4. What key questions did you have about your audience(s) and what information did

you gather about your target audience? How did you gather it? What are the strengths and limitations of what you know about them?

5. Clear presentation of your communication strategies. What principles of

communication are you recommending and why?

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6. Specific examples - this should include central messages, possible examples of print

or other media. 7. Delineation of how the plan will be evaluated. 8. Recommendations: how the client can use this information; how future students may

build on your work.



References must follow the publication style of the Professional Communication

Style (http://www.ieeepcs.org/activities_publications_transactions_authors.php). Any source which appears in the text must appear in the bibliography.



Personal Statement:


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1. Students are expected to take primary responsibility for the development of their capstone projects. You are expected to conceptualize, carry out, and report your projects. I suggest you formulate your project to help you in your academic career (e.g. thesis chapter, published paper, etc.).





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APPENDIX 13



NON-MARKET VALUATION OF BIODIVERSITY USING NON-TRADITIONAL VALUATION METHODS

To: Northern Great Plains Biosphere Research Group From: Dr. John Tyndall, Assistant Professor of Environmental Policy Dear Research Group: This research request has two main functions: one is to make an effort towards articulating the value of North Dakota’s biodiversity – past and present; the other is to make a “Data-Quality” policy statement regarding the use of various non-traditional socio-cultural economic valuation techniques. As a natural resource economist, I have a scholarly interest in the different ways that economists can qualify and quantify the economic value of something which is relatively nebulous – specifically biodiversity. I am aware of the now conventional methods of non-market environmental valuation, such as contingent valuation, hedonic modeling, travel-cost methods, cost aversion, etc.; however, I also have an interest in non-traditional ways of valuation – at least non-traditional in a neoclassical economic sense. I would like you to, using various methodologies of historians, ethno-botanists, and cultural anthropologists, articulate – qualitatively and, if possible, quantitatively – “traditional values” of North Dakota’s plant, animal, genetic, and ecosystem biodiversity. Specifically (with assistance in identifying these people) I would like you to interview members of key groups of “traditional knowledge keepers” – local historians, indigenous people, mid-20th century (or earlier) farmers. By providing a written recording of various forms of oral history and making a professional appraisal of your experience, specifically I would like you to provide the following:

o A qualitative assessment of the biodiversity “state of affairs” in North Dakota –

provide a historiography perspective. Provide a framework for an economic analysis that can use your data

o Address the issue of bio-prospecting and benefits sharing with regards to ND

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o Can non-traditional data collection such as this, provide beneficial insights into valuation and policy questions? How might one provide “confidence measures” in such data?

We will require a written assessment, formal presentation, and a policy brief (including a script that could be used as a basis for a television information spot). Our highly valued scientific and political advisors, Drs. Hanley, Tyndall, and Laguette will provide you with any additional details you might need. Please submit the required materials by the deadlines outlined by Dr. Hanley. Note: a state vehicle or a ride can be provided to you to conduct research. Human Subjects training and approval through IRB will likely be required – no big deal. Also, being a classic technophobe, I request that you are not to use the internet to collect info randomly – perhaps only to look up definitions.

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APPENDIX 14



LAB 2: GIS, AN INTRODUCTION What is a GIS?

In the strictest sense, a GIS is a computer system capable of assembling, storing, manipulating, and displaying geographically referenced information, i.e. data identified according to their locations. Practitioners also regard the total GIS as including operating personnel and the data that go into the system.

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Data Source: http://www.usgs.gov/research/gis/title.html How does a GIS work?

Relating information from different sources If you could relate information about the rainfall of your State to aerial photographs of your county, you might be able to tell which wetlands dry up at certain times of the year. A GIS, which can use information from many different sources, in many different forms can help with such analyses. The primary requirement for the source data is that the locations for the variables are known. Location may be annotated by x,y, and z coordinates of longitude, latitude, and elevation, or by such systems as ZIP codes or highway mile markers. Any variable that can be located spatially can be fed into a GIS. Federal agencies and private firms are producing several computer databases that can be directly entered into a GIS. Different kinds of data in map form can be entered into a GIS. A GIS can also convert existing digital information, which may not yet be in map form, into forms it can recognize and use. For example, digital satellite images can be analyzed to produce a map like layer of digital information about vegetative covers.

Likewise, census or hydrologic tabular data can be converted to map-like form, serving as layers of thematic information in a GIS.

Data Capture How can a GIS use the information in a map? If the data to be used are not already in digital form, that is, in a form the computer can recognize, various techniques can capture the information. Maps can be digitized, or hand-traced with at computer mouse, to collect the coordinates of features. Electronic scanning devices will also convert map lines and points to digits. A GIS can be used to emphasize the spatial relationships among the objects being mapped. While a computer-aided mapping system may represent a road simply as a line, a GIS may also recognize that road as the border between wetland and urban development, or as the link between Main Street and Blueberry Lane. Data capture - putting the information into the system - is the time-consuming component of GIS work. Identities of the objects on the map must be specified, as well as their spatial relationships. Editing of information that is automatically captured can also be difficult. Electronic scanners record blemishes on a map just as faithfully as they record the map features. For example, a fleck of dirt might connect two lines that should not be connected. Extraneous data must be edited, or removed from the digital data file.

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Data integration A GIS makes it possible to link, or integrate, information that is difficult to associate through any other means. Thus, a GIS can use combinations of mapped variables to build and analyze new variables.

Using GIS technology and Water Company billing information, it is possible to simulate the discharge of materials in the septic systems in a neighborhood upstream from a wetland. The bills show how much water is used at each address. The amount of water a customer uses will roughly predict the amount of material that will be discharged into the septic systems, so that areas of heavy septic discharge can be located using a GIS.

Projection and registration A property ownership map might be at a different scale from a soil map. Map information in a GIS must be manipulated so that it registers, or fits, with information gathered from other maps. Before the digital data can be analyzed, they may have to undergo other manipulations - projection conversions, for example - that integrate them into a GIS. Projection is a fundamental component of mapmaking. A projection is a mathematical means of transferring information from the Earth's three-dimensional curved surface to a two-dimensional medium - paper or a computer screen. Different projections are used for different types of maps because each projection is particularly appropriate to certain uses. For example, a projection that accurately represents the shapes of the continents will distort their relative sizes. Since much of the information in a GIS comes from existing maps, a GIS use the processing power of the computer to transform digital information, gathered from sources with different projections to a common projection.

Data structures Can a property ownership map be related to a satellite image, a timely indicator of land uses? Yes, but since digital data are collected and stored in various ways, the two data sources may not be entirely compatible. So a GIS must be able to convert data from one structure to another. Image data from a satellite that has been interpreted by a computer to produce a land use map can be "read into" the GIS in raster format. Raster data files consist of rows of uniform cells coded according to data values. An example would be land cover classification.

Raster data files can be manipulated quickly by the computer, but they are often less detailed an may be less visually appealing than vector data files, which can approximate the appearance of more traditional hand-drafted maps. Vector digital

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data have been captured as points, lines (a series of point coordinates), or areas (shapes bounded by lines). An example of data typically held in a vector file would be the property boundaries for a housing subdivision. Data restructuring can be performed by a GIS to convert data into different formats. For example, a GIS may be used to convert a satellite image map to a vector structure by generating lines around all cells with the same classification, while determining the cell spatial relationships, such as adjacency or inclusion. Thus a GIS can be used to analyze land use information in conjunction with property ownership information.

Data modeling It is difficult to relate wetland maps to rainfall amounts recorded at different points such as airports, television stations, and high schools. A GIS, however, can be used to depict two- and three-dimensional characteristics of the Earth's surface, subsurface, and atmosphere from information points. For example, a GIS can quickly generate a map with lines that indicate rainfall amounts.

Such a map can be thought of as a rainfall contour map. Many sophisticated methods can estimate the characteristics of surfaces from a limited number of point measurements. A two-dimensional contour map created from the surface modeling of rainfall point measurements may be overlain and analyzed with any other map in a GIS covering the same area.

What's special about a GIS?

The way maps and other data have been stored or filed as layers of information in a GIS makes it possible to perform complex analyses.

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Information retrieval What do you know about the swampy area at the end of your street? With a GIS you can "point" at a location, object, or area on the screen and retrieve recorded information about it from off-screen files.

Using scanned aerial photographs as a visual guide, you can ask a GIS about the geology or hydrology of the area or even about how close a swamp is to end of a street. This kind of analytic function allows you to draw conclusions about the swamp's environmental sensitivity.

Topological modeling In the past 35 years, were there any gas stations or factories operating next to the swamp? Any within two miles and uphill from the swamp? A GIS can recognize and analyze the spatial relationships among mapped phenomena. Conditions of adjacency (what is next to what), containment (what is enclosed by what), and proximity (how close something is to something else) can be determined with a GIS.

Networks If all the factories near a wetland were accidentally to release chemicals into the river at the same time, how long would it take for a damaging amount of pollutant to enter the wetland reserve? A GIS can simulate the route of materials along a linear network. It is possible to assign values such as direction and speed to the digital stream and "move" the contaminants through the stream system.

Overlay Using maps of wetlands, slopes, streams, land use, and soils, the GIS might produce a new map layer or overlay that ranks the wetlands according to their relative sensitivity to damage from nearby factories or homes.

Data output A critical component of a GIS is its ability to produce graphics on the screen or on paper that convey the results of analysis to the people who make decisions about resources. Wall maps and other graphics can be generated, allowing the viewer to visualize and thereby understand the results of analyses or simulations of potential events.

APPLICATIONS OF GIS Mapmaking

Researchers are working to incorporate the mapmaking experience of traditional cartographers into GIS technology for the automated production of maps.

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Using a GIS and digital versions of the 1:100,000 - scale transportation network, political boundaries, and hydrographic features, cartographers produced a 1:500,000 - scale standard base map of New Jersey. This digital revision was done in three steps of map scale reduction: 1:100,000, 1:250,000, and 1:500,000.

Each scale reduction required edge matching, or paneling, of the larger scale maps to produce the next small-scale map. In addition, through the process known as generalization, the amount of information was reduced to make the smaller scale map readable.

Site selection The U.S. Geological survey (USGS), in a cooperative project with the Connecticut Department of Natural Resources, digitized more than 40 map layers for the areas covered by the USGS Broad Brook and Ellington 7.5-minute topographic quadrangle maps.

This information can be combined and manipulated in a GIS to address planning and natural resource issues. GIS information was used to locate a potential site for new water well within half a mile of the Somers Water Company service area. To prepare the analysis, digital maps of the water service areas were stored in the GIS. Using the buffer function in the GIS, a half-mile zone was drawn around the water company service area. This buffer zone was the "window" used to view and combine the various map coverages relevant to the well site selection. The land use and land cover map for the two areas shows that the area is partly developed. A GIS was used to select undeveloped areas from the land use and land cover map as the first step in finding well sites. The developed areas were eliminated from further consideration. The quality of water in Connecticut streams is closely monitored. Some of the streams in the study area were known to be unusable as drinking water sources. To avoid pulling water from these streams into the wells, 100-meter buffer zones were created around the unsuitable streams using the GIS, and the zones were plotted on the map. The map showing the buffered zone was combined with the land use and land cover map to eliminate areas around unsuitable streams from the analysis. Point sources of pollution are recorded by the Connecticut Department of Natural Resources. hese records consist of a geographic location and a text description of the pollutant. To avoid these toxic areas, a buffer zone of 500 meters was established around each point.

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This information was combined with the previous two map layers to produce a new map of areas suitable for well sites. The map of surficial geology shows the earth materials that lie above bedrock. Since the area under consideration in Connecticut is covered by glacial deposits, the surface consists largely of sand and gravel, with some glacial till and fine-grained sediments. Of these materials, sand and gravel are the most likely to store water that could be tapped with wells. Areas underlain by sand and gravel were selected from the surficial geology map and combined with the results of the previous selections to produce a new overlay map consisting of sites in undeveloped areas underlain by sand and gravel that are more than 500 meters from point sources of pollution and more than 100 meters from unsuitable streams. A map shows that the thickness of saturated sediments was created by using the GIS to subtract the bedrock elevation from the surface elevation. For this analysis, areas having more than 40 feet of saturated sediments were selected and combined with the previous overlays. The resulting site selection map shows areas that are undeveloped, are situated outside the buffered pollution areas, and are underlain by 40 feet or more of water-saturated sand and gravel. Because of map resolution and the limits of precision in digitizing, the very small polygons (areas) may not have all of the characteristics analyzed, so another GIS function was used to screen out areas smaller than 10 acres. The final six sites are displayed with the road and stream network and selected place names for use in the field. The process illustrated by this site selection analysis has been used for a number of common applications, including transportation planning and waste disposal site location. The technique is particularly useful when several physical factors must be considered and integrated over a large area.

Emergency response planning The Wasatch Fault zone runs through Salt Lake City along the foot of the Wasatch Mountains in north-central Utah.

A GIS was used to combine road network and earth science information to analyze the effect of an earthquake on the response time of fire and rescue squads. The area covered by the USGS Sugar House 7.5-minute topographic quadrangle map was selected for the study because it includes both undeveloped areas in the mountains and a portion of Salt Lake City. Detailed earth science information was available for the entire area. The road network from a USGS digital line graph includes information on the types of roads, which range from rough trails to divided highways.

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The locations of fire stations were plotted on the road network, and a GIS function called network analysis was used to calculate the time necessary for emergency vehicles to travel from the fire stations to different areas of the city. The network analysis function considers tow elements: distance from the fire station, and speed of travel based on road type. The analysis shows that under normal conditions, most of the area within the city will be served in less than 7 minutes and 30 seconds because of the distribution and density of fire stations and the continuous network of roads. The accompanying illustration depicts the blockage of the road network that would result from an earthquake by assuming that any road crossing the fault trace would become impassable. The primary effect on emergency response time would occur in neighborhoods west of the fault trace, where travel times from the fire stations would be lengthened noticeably. The Salt Lake City area lies on lake sediments of varying thicknesses. These sediments range from clay to sand and gravel, and most are water saturated. In an earthquake, these materials may momentarily lose their ability to support surface structures, including roads. The potential for this phenomenon, known as liquefaction, is shown in a composite map portraying the inferred relative stability of the land surface during an earthquake. Areas near the fault and underlain by thick, loosely consolidated, water-saturated sediments will suffer the most intense surface motion during an earthquake. Areas on the mountain front with thin surface sediments will experience less additional ground acceleration. The map of liquefaction potential was combined with the road network analysis to show the additional effect of liquefaction on response times. The final map shows that areas near the fault, as well as those underlain by thick, water-saturated sediments, are subject to more road disruptions and slower emergency response than are other areas of the city.

Simulating environmental effects The National Forest Service was offered a land swap by a mining company seeking development rights to a mineral deposit in the Prescott National Forest of Arizona. Using a GIS and a variety of digital maps, the USGS and the Forest Service created perspective views of the area to depict the terrain before and after mining.

Existing digital data were combined in a GIS and displayed using a function that creates perspective drawings. The mining company provided planimetric (two-dimensional) drawings of the proposed mine. This plan was digitized, along with elevation information on the proposed mine and associated piles and ponds. The resulting perspective view illustrates the dramatic changes to the topography that mining would cause.

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A GIS can combine map types and display them in realistic three-dimensional perspective views that convey information more effectively and to wider audiences than traditional, two-dimensional maps.

Graphic display techniques Traditional maps are abstractions of the real world, a sampling of important elements portrayed on a sheet of paper with symbols to represent physical objects. People who use maps must interpret these symbols. Topographic maps show the shape of land surface with contour lines. The actual shape of the land can be seen only in the mind's eye. Graphic display techniques in GIS's make relationships among map elements visible, heightening one's ability to extract and analyze information. Two types of data were combined in a GIS to produce a perspective view or a portion of San Mateo County, California. The digital elevation model, consisting of surface elevations recorded on a 30-meter horizontal grid, shows high elevations as white and low elevation as black. The accompanying Landsat Thematic Mapper image shows a false-color infrared image of the same area in 30-meter pixels, or picture elements. A GIS was used to register and combine the two images to produce the three-dimensional perspective view looking down the San Andreas Fault.

SOME APPLICATIONS OF GIS AT UMAC Error Analysis for West Nile Virus spread prediction

A map projecting the spread of West Nile Virus (WNV) for the year of 2003 was derived by running Genetic Algorithm for Rule-set Prediction (GARP) model based on the data collected in the years 2001 and 2002. The results were checked with the ground truth data for the year 2003 available from The Center for Disease Control (CDC). This error analysis was done using a GIS system. The prediction has been done on a county wide scale. The analysis was based on the containment function of topographic analysis.

Applications in surface runoff calculation

GIS has been used to perform surface runoff modeling and calculations on varied scales here at UMAC. Analysis has been performed from single fields to major watershed areas (Devils lake basin). Running hydrological models would provide values for flow direction, flow accumulation, stream networks, sub-watersheds, etc. The calculations are performed using rigorous multiple iterations based on multiple input layers such as rainfall distribution, topography of the area, groundwater recharge, etc.

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These calculations have also been performed for various research projects calculating the water balance equation for different scale geographical regions. The calculations have been used to understand the water cycle in the region and to estimate the water loss due to evaporations and transpiration.

Area of interest (AOI) management and data distribution to end users

The end user community at UMAC mostly comprises of farmers and ranchers and other individuals closely related to the agricultural industry such as insurance agents, etc. All the users are encouraged to decide their AOI and then we make a boundary file for their AOI using x,y coordinates for the four corners. All the data distribution to the end users is done based on their AOIs. Data is clipped to the exact boundary for their AOI so as to reduce the amount of data required to download to the actual size of their AOI. This saves lot of time and band width. AOI management is done using GIS and new AOIs are constantly added for the new end users joining our group.

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LAB ASSIGNMENT: Mapping species richness patterns using ArcView

Introduction

In this lab, we will analyze basic biodiversity data. Specifically, we will look at the spatial distribution of biodiversity data by mapping the country-by country values previously studied.

The purpose of this exercise is to explore a file of biodiversity data to determine patterns of species numbers in space and time. We will be testing hypotheses of the factors determining species richness. In this exercise we will determine some of the large-scale relations between environmental gradients and species richness; at the same time we will be learning how this kind of question can be investigated.

Data and Methods

(1) Import data into ArcView. – The provided file is in CSV (Comma delimited) format suitable for import into ArcView. It was created as follows: Biodiversity Data.xls and saved as a CSV format in Excel. It was then brought into ArcView where it was joined to the world layer, which is an ArcView layer with the countries of the world and their surface area. Incidentally, this was not a straightforward procedure. First I had to ensure the spelling of the various countries was the same, including details such as "Korea PDR" was changed to "Korea, Peoples Democratic Republic". Some countries had changed their names (Burma is now Myanmar, for example), and others missing in one file of the other (ArcView does not have boundaries for many small countries of the world, especially small Islands). Next the data was exported to Excel, where details such as missing data were dealt with. For the purpose of this assignment, Biodiversity Data.csv (see appendix 1) has been updated to match the country names in the "cntry92.shp" file that you will be using for analysis.

Assignment

The assignment is relatively simple, but you will need to think carefully about the data. The first task is to plot the spatial patterns of species richness of mammals, birds, reptiles and amphibians.

(2) Analysis Steps.

a. You need to join the species richness table to a world map in ArcView. Launch ArcView, add a world map to the Table of Contents by clicking on

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the “add data” button and navigating to c:/esri/esridata/world/cntry92. Next, you will need to add Table 13-1.csv. This is done the same way as

for the world layer above. Click on and navigate to Table 13-1.csv and add it to your Table of Contents.

Table Biodiversity Data.csv has been edited to include mammals, birds, reptiles and amphibians normalized by area. This was done in Excel by dividing each value of mammals, birds etc. for each country by the area of the country, and multiplying it by 100,000. This avoided having very small values that are difficult to plot. It is always important to make note of any changes that have been made to the data you are working with.

b. Now, you want to join the information from Table 13-1.csv to the world map layer. Select the cntry92 layer in the Table of Contents and right-click your mouse button. Then, select “Joins and Relates►Join…”. Make sure the information in the dialog box is the same as this:

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Here, you are joining the data in Biodiversity Data.csv to the cntry92 layer.

c. Now, right-click on Cntry92, select “Properties” and select the tab “Symbology”. You want to select “Quantities/Graduated Colors”, and under “Value” you will select the appropriate field to answer the questions below (ie. mammals, birds, reptiles, amphibians, mamnorm, birdnorm, repnorm, amphnorm).

You will need to be concerned with re-defining the classes of your maps, and this can be done under the Symbology tab in ArcView. On the right hand side of the “Symbology” dialog box there is a box called

“Classification”, select , and the following dialog box appears:

Here you can use the histogram to determine the breaks that appear in your legend, or use the break values on the right.

d. You'll need to account for the countries with missing data. Missing data is represented by a –99 in Biodiversity Data.csv. Therefore, this will show

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up when you are classifying your data in ArcView. By keeping all negative numbers in one class, you can rename that class in “Symbology” as No Data. Under “Label” simply double-click on the first values in the list and then you are able to type in the label that you want to appear in your Table of Contents. This is also what will show up in your legend. Now you are ready to set up your species diversity maps in layout for printing.

Questions

Aside from the maps, you should be able to answer ALL questions on one page, single spaced. Double spacing is not required, but if you choose to do so, you are allowed a MAXIMUM of two pages. Also, you should include a couple of sentences for methodology (what software the maps were prepared in; where the data was from – remember, maps are data too; what calculations were performed on the data, etc.).

Make maps of the spatial distribution of biodiversity of mammals, birds, reptiles and amphibians. Are there anomalous values, and why do you think they are there? By anomalous we mean are the results inconsistent or deviating from what would be expected. Think about these questions and comment, where necessary for questions 1 and 2. DO NOT turn these maps in.

(1) Create a choropleth map of the data normalized by area. Make maps of the spatial distribution of biodiversity of mammals, birds, reptiles and amphibians. This should be done in layout view. These maps should be turned in, so prepare them accordingly (Please include all components that you see on professional maps): (5 pts.)

• What are the spatial patterns of biodiversity (describe the patterns on the maps)? (3 pts.)

• Do the 4 groups of vertebrates show similar patterns? (1 pt.)

(2) What can we learn from these data, and what are problems with our analysis (and perhaps our conclusion)? First, keep in mind the data. Since biodiversity is a scale dependent phenomenon, it is a bit problematic to compare data from large countries such as the USSR (former Soviet Union) or Canada with small countries such as Monaco or Guam. Normalizing the data by area helped, but it must be easier to get an accurate count in small countries than large ones. (3 pts.)

(3) What other problems are there with these data? Then think about the quality of

the data. Where are the missing data? These data have been compiled from many sources and have been collected over the past two centuries, although the pace of scientific research has accelerated in more recent decades. Where are

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the better collections? You can perhaps understand if there are no data from Angola, where there has been a war going on for decades, and where there are millions of land mines scattered through the landscape. (3 pts.)

(4) Are there other such areas where you can reasonably explain these data? (3 pts.)

(5) Are data missing from countries where you would suspect there should be good data? (2 pts.)

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Appendix 1. Country-by-country list of the total number of species (species richness) of mammals, birds, reptiles, and amphibians.

COUNTRY AREA MAMMAL BIRD REPTILES AMPHIBIANS MAMNORM BIRDNORM REPNORM AMPHNORM

Afghanistan 249503 123 456 103 6 49.3 182.76 41.28 2.4

Albania 10772 68 215 31 13 27.25 86.17 12.42 5.21

Algeria 891693 92 192 -99 -99 36.87 76.95 -99 -99

Angola 476840 276 872 -99 -99 110.62 349.49 -99 -99

Antarctica 4718827 -99 -99 0 0 -99 -99 0 0

Argentina 1071584 258 -99 -99 123 103.41 -99 -99 49.3

Australia 2958532 282 571 700 180 113.02 228.85 280.56 72.14

Austria 32782 83 227 14 20 33.27 90.98 5.61 8.02

Bangladesh 52466 109 354 119 19 43.69 141.88 47.69 7.62

Belgium 12092 58 180 8 17 23.25 72.14 3.21 6.81

Belize 8543 125 528 107 -99 50.1 211.62 42.89 -99

Benin 44805 188 630 -99 -99 75.35 252.5 -99 -99

Bhutan 14789 109 448 19 24 43.69 179.56 7.62 9.62

Bolivia 421161 280 1257 250 110 112.22 503.8 100.2 44.09

Botswana 227569 154 569 143 36 61.72 228.05 57.31 14.43

Brazil 3251214 394 1573 468 502 157.91 630.45 187.57 201.2

Brunei 2600 155 359 44 76 62.12 143.89 17.64 30.46

Bulgaria 46115 81 242 33 17 32.46 96.99 13.23 6.81

Burkina Faso 106765 147 497 -99 -99 58.92 199.2 -99 -99

Burma 253446 300 867 203 75 120.24 347.49 81.36 30.06

Burundi 10923 107 633 -99 -99 42.89 253.7 -99 -99

Cambodia 70393 117 305 82 28 46.89 122.24 32.87 11.22

Cameroon 178767 297 848 -99 -99 119.04 339.88 -99 -99

Canada 3702824 139 426 41 40 55.71 170.74 16.43 16.03

Central African Republic 243895 209 668 -99 -99 83.77 267.73 -99 -99

Chad 489736 134 496 -99 -99 53.71 198.8 -99 -99

Chile 258251 91 432 78 29 36.47 173.14 31.26 11.62

China 3607953 394 1100 282 190 157.91 440.88 113.02 76.15

Colombia 445382 359 1721 383 407 143.89 689.77 153.51 163.12

Congo 127092 200 500 -99 -99 80.16 200.4 -99 -99

Costa Rica 19508 205 848 214 162 82.16 339.88 85.77 64.93

Cuba 38776 31 159 100 41 12.42 63.73 40.08 16.43

Cyprus 3545 21 80 23 4 8.42 32.06 9.22 1.6

Czechoslovakia 49424 81 277 12 19 32.46 111.02 4.81 7.62

Denmark 12513 43 185 5 14 17.23 74.15 2 5.61

Djibouti 8304 -99 311 -99 -99 -99 124.65 -99 -99

Dominican Republic 17512 20 125 -99 -99 8.02 50.1 -99 -99

Ecuador 96025 271 1435 337 343 108.62 575.14 135.07 137.47

Egypt 386286 102 132 83 6 40.88 52.91 33.27 2.4

El Salvador 8064 135 450 73 23 54.11 180.36 29.26 9.22

Equatorial Guinea 9510 184 392 -99 -99 73.75 157.11 -99 -99

Estonia 14959 -99 -99 -99 -99 -99 -99 -99 -99

Ethiopia 488139 255 836 -99 -99 102.2 335.07 -99 -99

Finland 128771 60 230 5 5 24.05 92.18 2 2

France 212659 93 267 32 32 37.27 107.01 12.83 12.83

French Guiana 31921 152 -99 -99 -99 60.92 -99 -99 -99

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Gabon 98838 190 617 -99 -99 76.15 247.29 -99 -99

Gambia, The 3866 108 489 -99 -99 43.29 195.99 -99 -99

Germany 135096 76 237 12 20 30.46 94.99 4.81 8.02

Ghana 90933 222 721 -99 -99 88.98 288.97 -99 -99

Greece 40595 95 244 51 15 38.08 97.79 20.44 6.01

Greenland 806568 -99 -99 -99 -99 -99 -99 -99 -99

Guatemala 41860 184 480 231 88 73.75 192.38 92.58 35.27

Guinea 98002 190 529 -99 -99 76.15 212.02 -99 -99

Guinea-Bissau 10898 108 376 -99 -99 43.29 150.7 -99 -99

Guyana 81006 193 -99 -99 -99 77.35 -99 -99 -99

Haiti 9916 20 -99 -99 -99 8.02 -99 -99 -99

Honduras 43710 173 -99 152 56 69.34 -99 60.92 22.44

Hungary 36899 72 203 15 17 28.86 81.36 6.01 6.81

Iceland 38755 11 80 0 0 4.41 32.06 0 0

India 1216700 317 969 389 206 127.05 388.37 155.91 82.56

Indonesia 655358 515 1519 511 270 206.41 608.81 204.81 108.22

Iran 623447 140 -99 164 11 56.11 -99 65.73 4.41

Iraq 170324 81 145 81 6 32.46 58.12 32.46 2.4

Ireland 26184 25 141 1 3 10.02 56.51 0.4 1.2

Israel 12021 -99 169 -99 -99 -99 67.73 -99 -99

Italy 114335 90 254 40 34 36.07 101.8 16.03 13.63

Ivory Coast 121068 -99 -99 -99 -99 -99 -99 -99 -99

Jamaica 3489 22 159 -99 -99 8.82 63.73 -99 -99

Japan 138363 90 250 63 52 36.07 100.2 25.25 20.84

Jordan 34564 -99 132 -99 -99 -99 52.91 -99 -99

Kenya 230614 309 1067 187 88 123.85 427.65 74.95 35.27

Korea, Republic of 35253 -99 -99 19 13 -99 -99 7.62 5.21 Korea, Democratic People's Republic of 49019 49 -99 18 13 19.64 -99 7.21 5.21

Kuwait 6229 -99 27 29 2 -99 10.82 11.62 0.8

Laos 89239 173 481 66 37 69.34 192.78 26.45 14.83

Latvia 24074 -99 -99 -99 -99 -99 -99 -99 -99

Lebanon 3959 52 124 -99 -99 20.84 49.7 -99 -99

Lesotho 11756 33 288 -99 -99 13.23 115.43 -99 -99

Liberia 35152 193 590 62 38 77.35 236.47 24.85 15.23

Libya 624835 76 80 -99 -99 30.46 32.06 -99 -99

Lithuania 25020 -99 -99 -99 -99 -99 -99 -99 -99

Luxembourg 1041 55 130 7 14 22.04 52.1 2.81 5.61

Madagascar 223560 105 250 252 144 42.08 100.2 101 57.71

Malawi 42840 195 630 134 69 78.16 252.5 53.71 27.65

Malaysia 124769 264 501 268 158 105.81 200.8 107.41 63.33

Mali 482377 137 647 16 -99 54.91 259.32 6.41 -99

Mauritania 394924 61 59 -99 -99 24.45 23.65 -99 -99

Mexico 742519 439 961 717 284 175.95 385.17 287.37 113.83

Mongolia 601706 -99 -99 -99 -99 -99 -99 -99 -99

Morocco 158870 105 209 -99 -99 42.08 83.77 -99 -99

Mozambique 301573 179 666 -99 62 71.74 266.93 -99 24.85

Namibia 309843 154 640 -99 32 61.72 256.51 -99 12.83

Nepal 56912 167 629 80 36 66.93 252.1 32.06 14.43

Netherlands 12735 55 187 7 16 22.04 74.95 2.81 6.41

New Zealand 96141 -99 285 40 3 -99 114.23 16.03 1.2

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Nicaragua 47031 -99 -99 161 59 -99 -99 64.53 23.65

Niger 456457 131 473 -99 -99 52.5 189.58 -99 -99

Nigeria 350733 274 831 100 60 109.82 333.06 40.08 24.05

Norway 134944 54 235 5 5 21.64 94.19 2 2

Oman 119470 46 -99 64 -99 18.44 -99 25.65 -99

Pakistan 336399 151 476 143 17 60.52 190.78 57.31 6.81

Panama 28310 218 922 226 164 87.37 369.53 90.58 65.73

Papua New Guinea 163275 242 578 249 183 96.99 231.66 99.8 73.35

Paraguay 155574 156 650 120 85 62.52 260.52 48.1 34.07

Peru 503049 344 1705 298 241 137.87 683.36 119.44 96.59

Philippines 89642 166 395 193 63 66.53 158.31 77.35 25.25

Poland 118022 85 224 9 18 34.07 89.78 3.61 7.21

Portugal 35947 63 214 29 17 25.25 85.77 11.62 6.81

Puerto Rico 3072 13 94 46 22 5.21 37.67 18.44 8.82

Qatar 3901 -99 -99 17 -99 -99 -99 6.81 -99

Romania 89444 84 249 25 19 33.67 99.8 10.02 7.62

Rwanda 10534 151 669 -99 -99 60.52 268.13 -99 -99

Saudi Arabia 738518 -99 59 84 -99 -99 23.65 33.67 -99

Senegal 81582 155 625 -99 -99 62.12 250.5 -99 -99

Sierra Leone 26679 147 614 -99 -99 58.92 246.09 -99 -99

Somalia 246958 171 639 193 27 68.54 256.11 77.35 10.82

South Africa 473525 247 774 299 95 99 310.22 119.84 38.08

Spain 187441 82 275 53 25 32.87 110.22 21.24 10.02

Sri Lanka 23921 86 221 144 39 34.47 88.58 57.71 15.63

Sudan 968058 267 938 -99 -99 107.01 375.95 -99 -99

Suriname 57722 187 -99 -99 -99 74.95 -99 -99 -99

Swaziland 6635 47 381 109 39 18.84 152.7 43.69 15.63

Sweden 167420 60 249 6 13 24.05 99.8 2.4 5.21

Switzerland 16005 75 201 14 18 30.06 80.56 5.61 7.21

Syria 74889 -99 165 -99 -99 -99 66.13 -99 -99

Taiwan 12711 62 160 67 26 24.85 64.13 26.85 10.42

Tanzania, United Republic of 364692 306 1016 245 121 122.64 407.21 98.2 48.5

Thailand 195367 251 616 298 107 100.6 246.89 119.44 42.89

Togo 23281 196 630 -99 -99 78.56 252.5 -99 -99

Trinidad 1875 100 258 -99 -99 40.08 103.41 -99 -99

Tunisia 59940 78 173 -99 -99 31.26 69.34 -99 -99

Turkey 305181 116 284 102 18 46.49 113.83 40.88 7.21

Uganda 92854 315 989 119 44 126.25 396.39 47.69 17.64

Union of Soviet Socialist Republics 8326645 276 -99 168 37 110.62 -99 67.33 14.83

United Arab Emirates 39606 -99 -99 37 -99 -99 -99 14.83 -99

United Kingdom 84610 50 219 8 7 20.04 87.77 3.21 2.81

United States 3629625 349 650 -99 -99 139.88 260.52 -99 -99

Uruguay 67750 81 -99 -99 -99 32.46 -99 -99 -99

Venezuela 358883 288 1308 -99 -99 115.43 524.24 -99 -99

Vietnam 128636 273 638 180 80 109.42 255.71 72.14 32.06

Western Sahara 102597 15 60 -99 -99 6.01 24.05 -99 -99

Yemen 151110 -99 -99 77 -99 -99 -99 30.86 -99

Yugoslavia 97833 95 245 41 23 38.08 98.2 16.43 9.22

Zaire 905921 415 1086 -99 -99 166.33 435.27 -99 -99

Zambia 293554 229 732 -99 83 91.78 293.38 -99 33.27

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APPENDIX 15 Lab # 4 Advanced GIS Applications Lab The goal: create new layer of information based on known information and according to specific

rules.

1. The ERDAS Imagine Model Maker

2. Tool Box

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3. Insert raster file

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4. Insert vector file

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5. Operations among spatial files

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6. Writing model to determine the class for each pixel.

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7. The resulted raster

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Lab # 5

The goal: Preparing a map for printing. The items that should be include in print out map: 1. Legend; Scale bar (not scale text !); North arrow; Location map or coordinate grid net. 2. Title (some time in the document and not in the map itself, could be just a title and could be title plus exploitation), Reference or source; Places or important locations as reference.

Switch to map view instead of data view. a. Insert = > Legend b. Insert = > Scale bar c. Insert = > North Arrow d. Map properties (right click on the mouse when highlight the map) => Grid e. Insert = > Text or text icon in the Draw menu

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APPENDIX 16



Assignment #3: Op-Art of Environmental-Related Graphic or Advertisement

Your assignment is to select an environmental-related graphic or advertisement from a

newspaper, magazine, or website. This can be essentially any environmental-related graphic or ad you would like; however, it should fit on one page. Using this graphic or ad, you will produce an op-art piece that explains the communication mechanisms, successes, failures, or other interesting communication points. For example:

What message(s) is the text attempting to communicate? Can you identify the intent of the text?

Who or what is the target audience of the text? Using some model of communication, what assumptions is the sender making about the

receiver? Is there a feedback mechanism? What messages (if any) does it communicate about nature or ecosystems? What techniques or strategies does it use? In your estimation, how effective is it?

By op-art piece, I am referring to an opinion piece like the one shown below originally published in

the New York Times. I am not referring to art movement of the 1960s that exploited the fallibility of the eye through the use of optical illusions.

Palm Beach County Ballot, 2000 Presidential Election

Bush is first on the ballot, and the punch dot for the Republicans Is also first. This is a good design, making it highly unlikely that a Bush voter would make an error.

The Democrats are listed second, but the correct punch dot for them is third. Since it is logical to assume that one punches the second dot on the ballot to vote for them, this is an

f l d i

Arrows look decorative, not

Since the English language is read from left to right, it is natural to expect that the dot will appear after the name. The sudden shift in the pattern – putting the Dots for the right column on the left – is likely to confuse voters

This is the logical place for the dots corresponding to the second column of party Listings. (Florida law actually specifies that voters must mark the box to the right of the ballot. The county election officials foolishly violated this law.)

** Many official bodies and corporations approve products or documents that are incompletely designed. When a design causes problems for a significant number of people, even if it was “approved,” the product is usually recalled, and sometimes reparations are made.

Modified from New York Times (11/14/2000), Paula Scher, Op-Art

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The example above is of one style that could be used. You are free to use whatever style you would like that addresses the communication mechanisms, successes, failures, or other interesting communication points.

Your op-art piece should be printed within 36” by 48” and include the original graphic or

advertisement (scanned). You will be free to use the color poster printer in the ESSP geospatial lab to print out your piece. This assignment is due on October 20, 2005 in class. During this class, you will briefly describe your op-art piece (~5-10 minutes only) and field any questions.

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APPENDIX 17



NATURE-BASED TOURISM IN THE PEMBINA GORGE, NORTH DAKOTA To: Northern Great Plains Biosphere Research Group From: North Dakota Parks and Recreation Department Dear Research Group:

On Friday August 20, 2004, Gov. John Hoeven announced that the state will help fund a trails planning study of the Pembina Gorge area. This study is a step in a process that was started in 2002 to develop nature-based tourism in the state. “Pembina Gorge is a treasure on North Dakota’s landscape, and we need to find ways to make them more accessible to all,” Hoeven said. We are pleased to announce that your organization has been awarded the cooperative agreement to carry out this study.

Specifically, the North Dakota Parks and Recreation Department needs the

following:

• An inventory of existing trails • Identify corridors for potential trail systems, keeping in mind cultural, historical,

and archaeological features of the region • A generalized environmental risk assessment for the proposed corridors • Estimate potential recreational demand • Determine potential carrying capacity for recreational use • Benefit cost analysis based on estimated demand figures

We want to minimize the impact of the proposed areas as much as possible,

while at the same time giving people an opportunity to see areas of interest. Please consider all types of trails, including walking, hiking, biking, horseback riding, water, and all-terrain vehicles.

We will require a written recommendation, formal presentation, and a policy brief

(including a script that could be used as a basis for a television information spot). Our highly valued scientific and political advisors, Drs. Hanley, Tyndall, and Laguette will provide you with any additional details you might need. Please submit the required materials by the deadlines outlined by Dr. Hanley.

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APPENDIX 18



News from the University of North Dakota Office of Communications 22 Twombly hall. Grand Forks, ND 58201 Telephone 777.777.7777; Fax 777.777.7778

For immediate release: May 27, 2004 Media contact: Thomas J. Hobbes, (609) 258-5729, [email protected]

Media advisory: Climate experts can comment on 'Day After Tomorrow' UND scientists can help separate fact from fiction in new film

(Grand Forks, ND) The University of North Dakota is home to leading climate scientists who are available to comment on the upcoming summer movie "The Day After Tomorrow" and its portrayal of human-induced global climate change.

The film, which will be released May 28, 2004 presents an apocalyptic scenario of sudden climate change brought on by global warming. Much like how Michael Crichton’s 1992 blockbuster Jurassic Park sparked discussion between the scientific community and the general public regarding genetic cloning, this film is expected to generate the same furor in the context of global climate change. UND’s ESSP 502 class is listed among the scientists who will help distinguish between established scientific conclusions and the fictionalized aspects of the film. In preparation of meeting with the public in a Q & A forum which will take place in the UND MU Grand Hall on May 30, all participating scientists are invited to a pre-release screening beginning at 9 AM in room 220, Clifford Hall.

#### Lab Assignment: Your task is to identify the climate change scenarios (ramifications) portrayed in the film (as many as you can) - even when the film makers are taking some “creative” liberties with scientific understanding.

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In teams of 2, organize the information requested in tasks 1-4; prepare for task 5:

1) Briefly describe the scenario/ramification and its scientific premise as portrayed in the film.

2) Outline any flaws in the science within each of your identified scenarios above.

3) Describe the likely (or hypothesized) reality of each identified scenario based on current scientific evidence –be prepared to show evidence from the scientific literature (you may define “show” as you wish).

4) Answer the following question: Is this fictionalized account of complex environmental issues a good platform to discuss scientific issues with the general public?

5) Be as prepared as possible to face an audience of the general public for a Q & A session regarding issues brought up in the movie and global climate change in general. This will occur during the normal lab hours. This is going to be rather informal.

Each 2 person team is to turn in a paper copy of their responses to tasks 1-4 no later than March 30 (Note: think of this assignment as helping you study for your quiz). This lab assignment is worth 25 points. Since this lab is intended to be both fun and informative the emphasis on the grading will be on your ability to concisely and clearly articulate your responses, not on your ability to be comprehensive and exhaustive. Discuss at least three scenarios/ramifications in your replies to tasks 1-3. Cite all sources used. During the Q & A portion of this lab, which will take place during your lab hours, all of you are expected to participate in the answering of the questions posed by your audience. To ensure equal opportunity for full student panel participation, the moderator will allow ample opportunity for full student participation in the answering of a question. For example, if one member of your panel takes the initiative to answer a particular question directly, feel encouraged to add to the discussion by offering your own scientific or philosophical “2¢” to the discussion – i.e. introduce new examples, introduce additional or new scientific, social or philosophical dimensions of the question not discussed. However, be prepared to be called upon by name. Learning Objectives:

• Experience and gain insights into a significant socio-environmental phenomenon: That is, the majority of our society (including many policy-makers) largely achieves understanding of environmental science and environmental issues through an assortment of both popular culture and media outlets (the internet is a major component of this dynamic) all with highly variable levels of “information quality”. An outcome of this social dynamic is that many discussions (and policies) in the environmental “arena” often revolve around half-truths, distortions, spurious correlations, agenda based points of view, and false or weak premises. Examples of the outcomes of this state of affairs are perhaps seen in the general societal disinterest (or worse, distrust) in environmental issues and in the politicization of science.

• Further expand our exploration of global environmental change. As always, if any of these objectives are not satisfactorily met please let us know!

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APPENDIX 19 Lab # 6 Advanced GIS Measurement Lab Creating buffer to map distance from land-use or landmark. Data available for this project are in: P:\ESSP_Public\Materials Block\Grand Forks GIS data The buffer command in GIS is useful to find area around a point, line or polygon. For example, in case of landfill allocation, it allows to map the entire area that is less than 2 mile from a road. Combination of two, or more, buffer maps could help to find a site that fit to two different conditions: buffer from roads and buffer from drainage network could reveal where the areas that are nearby roads but faraway from water. The buffer commands in ArcGIS 9 – there are two options, both in ArcToolbox: (1) Buffer (analysis) and (2) Multiple Ring Buffer. Open ArcToolbox and search for the buffer command by typing that name.

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The Buffer (analysis) command allow us to determine the buffer distance according to a linear distance (depends on the units the user is using) or a variable depended units, which relate higher distance to greater values.

The Multiple Ring Buffer command allows us to create different buffers:

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Combining the buffer layers will be with the “Union” command:

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Creating new variable with different values for each buffer area – the new Field will be added in the attribute table by right click of the mouse. The values will be zeros and they can be changed after activating the “start editing” from the Editor menu.

The new variable values could also be calculated from current variables

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The assignment is to find where in the AOI shape file, we can allocate landfill according to three layers: places, hydrology (rivers) and roads. You need to write a report that present your findings and explain the definition for each one of the variables that you use. The report is due to Wednesday, Feb. 2.

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APPENDIX 20


Block II: Biosphere’s Productivity Cycle-Dr. Hanley Student Led Discussion Evaluation: Fall 2005

Student: Paper: Grading Matrix for Student-Led Discussion 50 points possible

Criteria Max. pts. Your pts. Description of paper

• What’s the overall context/goal? • What is the question/hypothesis? • How is it evaluated?

15

Comments

Analysis of the information presented • Do the experiments/analysis address the

question? • Are the answers clear?

15

Comments

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Evaluation of conclusions • Are the conclusions justified? • How did this study advance the field? • What are the societal impacts or policy

implications, if any?

10

Comments

Organization and effectiveness of discussion • Logically orientated • Student participation

10

Comments

Overall Comments

Total Points

Possible 50

Score

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APPENDIX 21



Building bridges: the purpose of Earth system science

An example with the water cycle The water cycle can be understood as an open system regulated by its inputs and outputs. Every reservoir in the system is connected to the other reservoirs by fluxes. Each reservoir of the hydrologic system however is also part of other systems such as the atmosphere or the biosphere. Variations of some reservoirs parameters, such as temperature, concentration of elements (CO2, N2, etc.), and land use changes can induce changes in the systems’ balance, provoking cascade changes over the whole Earth System.

Nonetheless this scenario as articulated above is almost entirely focused on Earth science with seemingly little to do with the human component of this “system”. Yet, we have approached the water system from another perspective (albeit in a very brief and micro-costic way): socio-hydrologic cycling. Changes (such as fluxes and cascading effects) can be due to natural phenomena but change can also be induced by human activities, and changes (again fluxes and cascading effects) are manifest in

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many interrelated dimensions (biologic, hydrologic, geologic, sociologic – which includes the economic and the political, across time and space…).

What are the bridges linking the scientific aspect of the water system with this human, economical aspect? Your task is to concisely articulate (in an effective way of your choice) an example “bridge”.

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APPENDIX 22 Material Block: Movement of crop material from one year to another Assignment 5 – Mapping Nitrogen (N) credit for the Red River Valley The goal of this project is to prepare a method for UMAC N credit product. This product should map N credit on a large scale, in order to help end users to reduce their fertilization without affecting the yield. There are also environmental issues relating this product and it should include public awareness and education. Most of the research in the RRV is conducted on assessing sugar beet N credit, while other crops do not have much attention. As part of the Material block, the project should emphasize how to use current methods, to estimate N credit from the main crops in the valley. The main focal points are: • The importance of the N credit method for sustainability and how we can assess it • Differences among crops in the N credit importance, • How to assess N credit with remote sensing, • How to validate the product accuracy, and • How to create a friendly-user-product and assess it.

The results should be present by a short presentation (Tuesday, Feb 15th) and a paper (Wednesday, Feb 16th). The presentation should lead to discussion. Team: 3 members. Thursday – introduction to the sugar beet crop and the crop rotation. Friday – paper discussion, representing the main focal points. Monday – personal meeting with each group. Tuesday – presentation. Wednesday – paper submission. Thursday, Friday and Tuesday meetings at 9 a.m., room 220 Monday and Wednesday meetings at 9 a.m., room 310 (or 316)

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Papers: A. crop rotation and crop cycling –

Vos, J. and P. E. L. van der Putten (2000). "Nutrient cycling in a cropping system with potato, spring wheat, sugar beet, oats and nitrogen catch crops. I. Input and offtake of nitrogen, phosphorus and potassium." Nutrient Cycling in Agroecosystems 56: 87-97.

Franzen, D. W., J. F. Giles, L. J. Reitmeier, A. J. Hapka, A. J. Hapka, N. R. Cattanach and A. C. Cattanach (2001). "Summary of four years of research on poor quality sugarbeets in a sugarbeet, spring wheat, potato rotation." Sugarbeet Research and Extension Reports 32: 152-173.

Hapka, A. J., D. W. Franzen, J. F. Giles and N. R. Cattanach (2000). "Timing and release of nitrogen from residues." Sugarbeet Research and Extension Reports 31: 114-121.

Moraghan, J. T. and L. J. Smith (1996). "Nitrogen in sugarbeet tops and the growth of a subsequent wheat crop", Agronomy Journal 88: 521-526.

B. remote estimation of sugar beet N credit Sims, A.L., J. T. Moraghan and L. Smith (2002). "Spring wheat response to fertilizer

nitrogen following a sugarbeet crop varying in canopy color." Precision Agriculture 3: 283-295.

Franzen, D. W., G. Wagner and A. Sims (2003), ”Application of a ground-based sensor to determine N credit from sugar beet”, Sugarbeet Research and Extension Reports 34. 119-123

Johnson, K.L., T. M. Leshuk, D. R. Bernhardson and A. W. Cattanach (2001), “Variable rate N application on wheat after sugarbeet – “putting research into practice”, Sugarbeet Research and Extension Reports 32. 116-120

Suggested points for discussion, Vas and van der Putten: • The introduction: the policy behind the research • Definition for nutrient balance • What are the research findings about each one of the crops and their capability for N credit? Suggested points for discussion, Sims, Moraghan and Smith: • The use of aerial photography: can it be applied to a large scale as the RRV? • What is the use of the remote sensing in this research? Is this method allowing quantifying of

N credit or can it be used for relative zones-mapping inside a field? • Can this research approach be used for remote sensing product evaluation?

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Good source on sugar beet in the RRV can be found in the Sugarbeet Research & Education Board. They conducting an annual conference, which is summarize in research reports:

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APPENDIX 23



Assignment #4: Letter to the Editor

Letters to the editor of newspapers are an excellent means for commenting on environmental issues and making a point about a particular issue. Letters from readers have been shown to be one of the most widely read sections of newspapers, and have the potential of reaching particularly large audiences. They also have the ability to influence readers in ways regular articles in the newspaper cannot and help move or set a community agenda. In fact, President Clinton once remarked that his reelection campaign in 1996 was crafted by reading letters to the editor of newspapers around the country.

Your assignment is to write a letter to the editor of a newspaper (local-Grand

Forks Herald, or national-New York Times) dealing with your final project. This letter can advocate a particular position from your project or draw attention to a particular problem or issue. Specifically, you should comment on the communication aspects of the issue you choose. As usual, your letter will be graded based on the quality of the background information, description of the message, context of the message, and overall organization of the letter. Your letter should be brief and to the point and adhere to the length requirements of the newspaper for which you choose to write.

Your letter will be due on November 10. In that class, you will give a brief presentation of your letter (≤10 minutes in length).

After your letter is graded and editorial suggestions are provided, you will have

one week to submit it for publication in the newspaper of your choice. If you choose to submit it for publication and you provide evidence of the submission, you will receive an additional 5 points extra credit.

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DEPARTMENTAL PLAN FOR ASSESSMENT OF STUDENT LEARNING 2005-2006 ACADEMIC YEAR

Department: EARTH SYSTEM SCIENCE AND POLICY 1. Mission Background – The 20th century was extraordinary in that a single species became the dominant force in modifying the global environment1. Humans have transformed between one-third and one-half of the Earth’s land surface; changed the chemical composition of the atmosphere (each breath today has 30% more carbon dioxide than before the Industrial Revolution); fix as much atmospheric nitrogen as do all natural causes combined; overexploit at least a fifth of the world’s marine fisheries; use more than half of all available freshwater; and have facilitated a mass extinction event that is 100-1000 times the background rate2. It is now clear that humanity is changing the world faster than it can understand the consequences. A new way of thinking about the world has become increasingly common in order to solve the complex resource and environmental problems that we collectively face. Although substantial progress has been made towards understanding, protecting, and restoring our common environment, immense challenges still lie ahead. In order to better predict the consequences of our actions, it has become necessary to treat the Earth as a system of integrated components that are interdependent, rather than the sum of discrete parts that act independently. Consequently, a new kind of education has arisen to prepare citizenry to accept responsibility for management of the planet. What is Earth System Science and Policy? – The Earth System Science and Policy (ESSP) graduate program is intellectually centered on the science and policy of environmental sustainability. Sustainability science focuses on the dynamic interactions between nature and society by meeting human needs and values while preserving the planet’s life support systems3,4. The central goal of environmental sustainability is to live off nature’s interest rather than off its capital, thereby keeping intact the vital ecosystem services that nature provides. Sustainability science is, consequently, committed to a problem-driven agenda and is not confined to exclusively ‘applied’ research. In fact, pursuing solutions to practical, real-world sustainability problems is driving the science to address an array of fundamental questions. For example, what determines the vulnerability or resilience of the

1 McNeill, J. R. 2000. Something New Under the Sun: An Environmental History of the Twentieth-Century World. W.W. Norton & Co., New York. 2 Vitousek, P. M. et al. 1997. Human domination of Earth’s ecosystems. Science, 275: 494. 3 Kates, R. W. et al. 2001. Sustainability science. Science, 292: 641-642. 4 Clark, W. C., and N. M. Dickson. 2003. Sustainability science: The emerging research program. Proceedings of the National Academy of Sciences USA, 100: 8059-8061.

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nature-society systems in particular kinds of places and for particular types of ecosystems and human livelihoods?5 Sustainability science is an intellectually exciting, growing discipline that bridges scholarship and practice, global and local perspectives, and scientific and social disciplines to address a common theme: meeting the needs of society while sustaining the life support systems of the planet by building an understanding of the relationship between nature and society. The graduate program in Earth System Science and Policy is organized around the field of environmental sustainability and offers three degrees: Master of Environmental Management, Master of Science, and Doctor of Philosophy. This relatively new program grew out of a recognized need for comprehensive research and educational programs that provide practical engagement in research and management of the Earth system and resources. An editorial from the American Association for the Advancement of Science concluded that “it is hard to imagine a more important discipline than Earth System Science.”6 A presidential address to the AAAS linked the human prospect to “new ways of thinking-an integrated multidimensional approach to the problems of global sustainability.”7 In a 1993 report of the National Research Council on Solid-Earth Sciences and Society, a major conclusion was “this [Earth System Science] process-orientated, integrated, global approach should be incorporated into revised earth science curricula in universities and schools.” A 1998 report of the Earth System Sciences Committee of the NASA Advisory Council recommended that NASA undertake a comprehensive research program and called for a major new synthesis and understanding of the Earth system.” Many of the committee’s recommendations were implemented and NASA created the Earth System Enterprise program. In addressing public concerns about environmental issues, including air and water pollution, nuclear waste disposal, the ozone hole, invasive plants and animals, biodiversity, and global climate change, the scientific community has realized how interrelated the components of the Earth’s systems are. While the critical parts – processes in the biosphere, hydrosphere, atmosphere, and lithosphere – are studied in detail within the boundaries of traditional disciplines, how the parts combine and interact is the key to understanding how our planet works, its past history, and its likely future. The idea of “Earth System Science” has emerged, not as a loosely anchored “interdisciplinary” subject, but as the driving concept for major international scientific and policy efforts. Scientists also now recognize that economic and public policies, initiated either by individuals or their governments, have environmental consequences; and that, conversely, environmental parameters inescapably bound economic and political policies.

5 Turner, et al. 2003. A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences USA, 100: 8074-8079. 6 Lawton, J. 2001. Editorial: Earth system science. Science, 292: 1965. 7 Raven, P. H. 2002. Science, sustainability, and the human prospect. Science, 297: 954-958.

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2. Program Objectives The Earth System Science and Policy graduate program was organized in response to the developing integrated, interdisciplinary approach to understanding and managing the Earth and is at the intersection between science and human needs and values. The educational focus of the program is thematic, emphasizing practical experience, student-centered learning, integration of knowledge across traditional disciplinary boundaries, and active dialogue both in and outside the classroom.

Mission Statement. – to provide an integrated and creative learning environment that fosters intellectual growth, critical thinking, and practical engagement in research and management of the Earth system and resources.

The ESSP program encourages students from diverse backgrounds and perspectives to work collectively on relevant problems with the common goal of serving humankind’s needs for an environmentally sustainable and prosperous future. To achieve the ESSP program’s mission, we apply strategies that target specific goals in the area of sustainability science and Earth System Science and Policy. The strategies are linked by a set of overarching organizing principles that are essential to all program activities.

Excellence in learning. In order to represent the full complexity of nature and sustainability science, crucial elements of program’s learning objectives include: a student-structured curriculum, a multi-disciplinary teaching approach, and experiential learning environments.

Excellence in discovery. Research within the program is driven by societal needs and

values and occurs within an Earth System Science paradigm, in which the Earth is treated as a single system that cannot be understood by summing the features of its component parts.

Excellence in engagement. Through its outreach and service activities, one of the

chief aims of the program is to put knowledge to work creating new opportunities that advance society, solve scientific and social problems related to Earth System Science, and empower citizens to make informed decisions about their environment.

4

Given the broad mission statement and the overarching organizing principles of the ESSP program, specific program goals specify learning outcomes for graduates of the program. These program goals specify outcomes for the entire ESSP curriculum.

Earth System Science and Policy Program Goals

1. Students will possess a breadth of knowledge in Earth System Science and Policy and will be able to apply that knowledge to address societal-driven sustainability science research.

2. Students will have a strong foundation in basic science,

applications-driven science, geographical information systems (GIS), remote sensing, environmental policy, and statistics.

3. Students will gain valuable hands-on experiences and will

be able to conduct experimental work needed to substantiate theoretical developments.

4. Students will possess written and oral communication skills

that will help them present their ideas effectively to their peers and the public.

5. Students will be able to function within multidisciplinary

teams to accomplish goals of interest to the group. 6. Students will have skills and experience using cutting-edge

computer technology to solve complex research and applications problems.

7. Students will be aware of issues of scale associated with

environmental sustainability and Earth System Science and Policy (i.e. spatial, temporal, impact, etc.), and have a broad sense of their ethical and professional responsibilities.

8. Students will be aware and prepared for a lifetime of

learning.

5

3. Assessment Methods The Earth System Science and Policy graduate program utilize several assessment methods to evaluate learning outcomes for each of the program goals. Learning outcomes are routinely evaluated within the context of ESSP classes, especially ESSP 501 and 502. These courses are extraordinary in that between them they comprise 20 total credit hours of graduate coursework for each student. Each course is divided into three subject-related blocks that provide the students with the opportunity to learn about, experience, and practically deal with numerous sustainability-based research and policy problems. Individual faculty members who teach ESSP courses regularly evaluate course products and assignments with our program goals in mind. Regular faculty meetings, an annual faculty and staff retreat, and regular communication among faculty allow course instructors to share their assignments and discuss how they relate to the above program goals. Earth System Science & Policy Program Goals At the completion of a graduate degree in ESSP, students should be able to demonstrate that they can or possess:

Sample Individual Class Assessment Tools from ESSP Courses Course # Assignment Title/Description

1. a breadth of knowledge in Earth System

Science and Policy and will be able to apply that knowledge to address societal-driven sustainability science research

501 The Effect of Climate Change on

Biodiversity of North America block capstone project (Appendix 1)

501R Consumer Product Life Cycle Analysis 501L Alternative Fuels Fact Sheet 502 Mapping Nitrogen (N) Credit for the

Red River Valley 502R Economic Valuation of Water

Resources 502L CO2 in the Atmosphere – A Historical

Look Biogeochemistry Lab (Appendix 2)

520 Evaluation of Models Estimating Evapotranspiration

570 Sustainability Communications Capstone Project (Appendix 3)

594 Predictive Distributional Modeling of Vector-Borne Malaria Independent Study


998 Earth Science-Based Thesis Project

Sample Individual Class Assessment Tools, Correlated With Program Goals

6

2. a strong foundation in basic science,

applications-driven science, geographical information systems (GIS), remote sensing, environmental policy, and statistics

501 Research on the Mind lecture,

discussion, and lab assignment (Appendix 4)

501R Energy & Economy Lecture & Discussion

501L Introduction to GIS; Spatial Analysis of Ecosystem Productivity

502 GIS Definitions of Landscapes 502R GIS Applications Discussion 502L Global Temperature Change

Biogeochemistry Lab (Appendix 5) 520 Statistics Theory in Earth Modeling 570 Environmental Advertisement Analysis

(Appendix 6) 594 Research Literature Review 597 Semester Internship within the

professional environment 998 Earth Science-Based Thesis Project

3. valuable hands-on experiences and will be able

to conduct experimental work needed to substantiate theoretical developments

501 Dutch Elm Disease in Grand Forks 501R Energy Block Press Review 501L Species Predictive Distributional

Modeling (Appendix 7) 502 Micro-Economics of Bottled Water

(Appendix 8) 502R Full Cost Accounting Analysis of a

Hypothetical Landfill (Appendix 9) 502L Remote Sensing/GIS Lab 520 Earth Modeling Literature Review 540 Remote Sensing in the Developing

World 570 Analysis of Communications Models

Used in Environmental Messages 594 Predictive Distributional Modeling of

Vector-Borne Malaria 597 Semester Internship within the


7

4. written and oral communication skills that will

help students present their ideas effectively to their peers and the public

501 Biological Diversity Policy Debate

(Appendix 10) 501R Policy Brief Workshop 501L Biosphere Block Capstone

Presentation 502 Mapping Nitrogen (N) Credit for the

Red River Valley Formal Presentation 502R Land Use/Land Cover Discussion 502L Full Cost Accounting Assignment

Involving Solid Waste Management and the Issue of Landfilling Waste (Appendix 11)

520 Earth Modeling Review Paper 540 Remote Sensing Technologies

Presentation 570 Course Capstone Communications

Paper & Presentation (Appendix 12) 594 Professional Presentation: Predictive

Distributional Modeling of Vector-Borne Malaria


998 Written Thesis & Oral Defense

5. function within multidisciplinary teams to

accomplish goals of interest to the group

501 Sustainability Academic Controversy 501R Biosphere Block Capstone Projects

(Appendix 13) 501L Group work within labs 502 Landfill: Waste Materials & Decision

Making 502R Full Cost Accounting Analysis of a

Hypothetical Landfill 502L Hydrology of Devils Lake 520 Earth Model Development Project 540 Remote Sensing Reading Group 570 Environmental Ethics and Philosophy

Review & Discussion 597 Semester Internship within the

Professional Environment 998 Thesis data collection & analysis

8

6. skills and experience using cutting-edge

computer technology to solve complex research and applications problems

501 Biogeography: Predictive Distributional

Modeling 501R Energy Block Capstone Project poster

preparation 501L Introduction to GIS – Biosphere Block

Lab (Appendix 14) 502 GIS Definition of Landscape 502R North Dakota Waffle Project 502L Advanced GIS Applications Lab

(Appendix 15) 520 Statistics of Modeling 540 ERDAS IMAGINE/ArcMap Lab 570 Communications Analysis Poster

Presentation (Appendix 16) 594 Predictive Distributional Modeling

Algorithm Use 597 Semester Internship within the

Professional Environment 998 Thesis data analysis

7. awareness of issues of scale associated with

environmental sustainability and Earth System Science and Policy (i.e. spatial, temporal, impact, etc.), and have a broad sense of their ethical and professional responsibilities

501 Nature-Based Tourism in the Pembina

Gorge, North Dakota (Appendix 17) 501R Steam Generation Plant Field Trip &

Discussion 501L Biodiversity-Societal Impacts & Policy

Implications 502 Media advisory: Climate experts can

comment on 'The Day After Tomorrow' – A Science Review (Appendix 18)

502R Hydrology of Devils Lake Ethics Discussion

502L Advanced GIS Measurement Lab (Appendix 19)

520 Validation of a Modeling Result Using Remote Sensing Data

540 Fundamentals of Remote Sensing 570 Sustainability Ethics Lecture &

Discussion 594 Ethical Implications of Arboviral

Disease Distributional Modeling 597 Semester Internship within the

Professional Environment 998 Earth Science-Based Thesis Project

9

8. awareness and preparedness for a lifetime of

learning

501 Sustainability Book Club & Discussion

Group 501R Scientific Journal Student-Led

Discussion (Appendix 20) 501L The Rudiments of Research Biosphere

Lab 502 Building Bridges – The Purpose of

Earth System Science – An Example From the Hydrologic Cycle (Appendix 21)

502R Media advisory: Climate experts can comment on 'The Day After Tomorrow' – A Science Review

502L Movement of Crop Material From One Year to Another (Appendix 22)

520 Earth Modeling Complexity Discussion 540 Remote Sensing in the Developing

World 570 Letter to the Editor assignment

(Appendix 23) 594 Practical Application of Disease

Distributional Modeling 597 Semester Internship within the


Program learning outcomes are also evaluated within a myriad of other non-class program activities, including program-wide student presentations, participation in professional conferences, interactions with local stakeholders and user-groups, published professional papers, internships obtained and completed, placement within Ph.D. programs, and obtainment of jobs after graduation.

10

Appendices 1-24. Sample Individual Class Assessment Tools from ESSP Courses Appendix 1. The Effect of Climate Change on Biodiversity of North America block capstone project………..……….. 11 Appendix 2. CO2 in the Atmosphere- A Historical Look Biogeochemistry Lab………………………………………… 12 Appendix 3. Sustainability Communications Capstone Project………………………………………………………….. 18 Appendix 4. Research on the Mind lecture, discussion, and lab assignment…………………………………………….. 21 Appendix 5. Global Temperature Change Biogeochemistry Lab………………………………………………...........… 33 Appendix 6. Environmental Advertisement Analysis……………………………………………………………………. 37 Appendix 7. Species Predictive Distributional Modeling………………………………………………………...……… 38 Appendix 8. Micro-Economics of Bottled Water………………………………………………………………………… 45 Appendix 9. Full Cost Accounting Analysis of a Hypothetical Landfill………………………………………………… 46 Appendix 10. Biological Diversity Policy Debate……………………………………………….………………………. 52 Appendix 11. Full Cost Accounting Assignment Involving Solid Waste Management and the Issue of Landfilling

Waste………………………………………………………………………………………………………. 53 Appendix 12. Course Capstone Communications Paper & Presentation………………………………………………… 55 Appendix 13. Non-Market Valuation of Biodiversity Using Non-Traditional Valuation Methods……………………… 58 Appendix 14. Introduction to GIS – Biosphere Block Lab………………………………………………………………. 60 Appendix 15. Advanced GIS Applications Lab………………………………………………………………………….. 76 Appendix 16. Communications Analysis Poster Presentation………………………………………………………...…. 82 Appendix 17. Nature-Based Tourism in the Pembina Gorge, North Dakota………………….…………………………. 84 Appendix 18. Media Advisory: Climate Experts Can Comment on ‘The Day After Tomorrow’ – A Science

Review……………………………………………………………………………………………….…….. 85 Appendix 19. Advanced GIS Measurement Lab…………………………………………………………………………. 87 Appendix 20. Scientific Journal Student-Led Discussion………………………………………………………………... 93 Appendix 21. Building Bridges – The Purpose of Earth System Science – An Example From the Hydrologic Block…. 95 Appendix 22. Movement of Crop Material From One Year to Another…………………………………………………. 97 Appendix 23. Letter to the Editor Assignment…………………………………………………………………..……… 100

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APPENDIX 1



THE EFFECT OF CLIMATE CHANGE ON THE BIODIVERSITY OF NORTH AMERICA

TO: Northern Great Plains Climate Change/Biodiversity Research Group FROM: Kofi Annan, Secretary-General of the United Nations (UN) Dear Research Group:

The United Nations is in a never-ending race to make the world a better and safer place to live. The Division for Sustainable Development provides leadership and is an authoritative source of expertise within the United Nations system on sustainable development. Our goal is the integration of the social, economic and environmental dimensions of sustainable development in policy-making at the international, regional and national levels. For the same purpose, I am requesting premier organizations in various regions of the world to provide us with feedback of the effect of long term climate change on various life forms.

Specifically, I need to know the following:

• A generalized background to climate change projections as depicted by the Hadley Model for the years 2050 and 2080

• How might climate change effect the distribution of Mammals, Microbes, and Flora in North America and across the world (you can pick up one distinct type from each category)

• What are the policy recommendations you would like to suggest concerning this distribution due to climate change keeping in mind the goal of sustainable development

I will require a written policy recommendation, formal presentation, and a policy brief

(including a script that could be used as a basis for a television information spot). My highly valued scientific and political advisors, Drs. Hanley, Tyndall, and Laguette will provide you with any additional details you might need. Please submit the required materials by the deadlines outlined by Dr. Hanley.

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APPENDIX 2



LAB 2: CO2 IN THE ATMOSPHERE – A HISTORICAL LOOK 1. Introduction

The scientific community has reached a strong consensus regarding the science of global climate change8. The world is undoubtedly warming. This warming is largely the result of emissions of carbon dioxide and other greenhouse gases from human activities including industrial processes, fossil fuel combustion, and changes in land use, such as deforestation. Continuation of historical trends of greenhouse gas emissions will result in additional warming over the 21st century, with current projections of a global increase of 2.5ºF to 10.4ºF by 2100, with warming in the U.S. expected to be even higher. This warming will have real consequences for the United States and the world, for with that warming will also come additional sea-level rise that will gradually inundate coastal areas, changes in precipitation patterns, increased risk of droughts and floods, threats to biodiversity, and a number of potential challenges for public health.

How did the scientific community come to such dire conclusions? Is it possible to

obtain a look at composition of Earth’s atmosphere before humans were able to take direct measurements? Ice core samples provide an uninterrupted source of data on important properties of paleoclimate, including local temperature and precipitation rate, humidity, and wind speed. Ice core samples also record changes in atmospheric composition. In this lab we will work with the original data from the famous Vostok Ice Cores, which carry the distinction of being the only ice cores that scientists are certain have remained undisturbed for the last interglacial and penultimate glacial periods9.

2. The Vostok Research Station

The Vostok research station is located near the south geomagnetic pole, at the center of the East Antarctic ice sheet, where the flux in the earth's electromagnetic field is manifested. It has the dubious distinction of being the coldest place ever recorded on the planet (-91°C or -131.8°F in 1997). The station was built in 1957 and named after one of the ships of F. G. von Bellinghausen, one of the original discoverers of Antarctica.

8 National Academy of Sciences, Commission on Geosciences, Environment and Resources., 2001. Climate Change Science: An Analysis of Some Key Questions. National Academy Press, Washington, D.C. 29 pp. 9 AGU, 1995.

13

The Vostok research station has operated year-round for more than 37 years. In the

1970s, researchers from the Soviet Union drilled a set of holes 500–952 m deep in the ice. These holes have been used to study the oxygen isotope composition of the ice, which showed that ice of the last glacial period was present below about 400 m depth. Three more holes were then drilled: in 1984, Hole 3G reached a final depth of 2202 m; in 1990, Hole 4G reached a final depth of 2546; and in 1993 Hole 5G reached a depth of 2755 m. Currently, a Russian, French, and American team of scientists is drilling an ice core through the 3,700 m thick ice sheet. The ice at the bottom of this core is estimated to be half a million years old. 3. Ice Core Samples

Ice cores are unique with their entrapped

air inclusions enabling direct records of past changes in atmospheric trace-gas composition. Ice samples are cut with a band saw in a cold room (at about -15°C) as close as possible to the center of the core in order to avoid surface contamination. Gas extraction and measurements were performed, which involved crushing the ice sample (~40 g) under vacuum in a stainless steel container without melting it, expanding the gas released during the crushing in a pre-evacuated sampling loop, and analyzing the CO2 concentrations by gas chromatography. LAB ASSIGNMENT

14

In this lab, you will analyze the original CO2 data from the Vostok ice core samples and answer a series of questions.

Part 1. Ice and CO2 in the Vostok Core

First, download the primary data file containing the Vostok ice core data (Public

Drive/ESSP_Public/Biogeochemical Block/Lab-CO2 in the Atmosphere…/vos_data.tsv). Save it onto your hard drive as a worksheet entitled: vosdata. Note: open the file in Excel (you may need to specify files of type: “All Files”). The data should be imported as delimited and tab-separated. Your Excel sheet should contain the following columns: depth (in meters) of the ice core, the “ice” and “gas” ages (in thousands of years), concentrations of CO2 and CH4 found in the ice bubbles, the deuterium isotopic ratios, and a column that provides information on dust. If you do not have this right now, then go back and try again.

The ice age (i.e. the age of the ice, which should not be confused with the use of the

term ice age as referenced by an ice sheet that moved down over northern latitudes a few thousand years ago) is obtained by counting layers of ice and modeling the flow of merging ice layers. The gas age is calculated assuming that the bubbles of gas can only be trapped effectively in layers of older ice (i.e. at a depth well below the surface where the pores of the ice close, thus sealing the air).

Now, you will plot both ice age and the gas age as a function of depth. First, select

the entire ice age column by clicking on “B” at the top of it, then hold down the control key, and then select the gas age column by clicking on the “E” at the top. Once both are selected, click on the “Chart Wizard” icon and select the first line graph (without markers) option. In step 2 of the “Chart Wizard”, modify the series data (click on the series tab) to use the depth values in column A as the category (X) labels. You will need to specify the numbers themselves, not the whole column. The formula for the X values for both series should look like this: =vos_data!$A$3:$A$196. Now click “Next,” and give your chart appropriate labels for the title and axes. Be sure to label appropriate units. If you do not know what they should be, then re-read this lab from the beginning. You should always know what you are graphing and why! Next, finalize your chart and print it out (full page) to turn with your answers to questions. [3 points]

Questions 1. The two age curves differ. Why? How much younger, roughly, is a bubble of gas

than the ice that surrounds it, and a depth of 1000 meters? [2 points]

Part 2. The Temperature Record

Ice in glaciers has an increased proportional abundance of heavy oxygen if it was deposited during relatively warm periods. To understand why this might be so, think about the process of glacier formation. The water-ice in glaciers originally came from the oceans as vapor, later falling as snow and becoming compacted in ice. When water evaporates, the heavy water (H2O18) is left behind and the water vapor is enriched in light water (H2O16). This is because it is harder for heavier water molecules to overcome the barriers of evaporation. Thus, glaciers are relatively enhanced in O16, while the oceans are relatively enriched in O18. This imbalance is more pronounced in colder climates than for warmer

15

climates. In fact, it has been shown that a decrease of one part per million O18 in ice reflects a 1.5°C drop in air temperature at the time it originally evaporated from the oceans.

Now we want to convert the deuterium isotopic ratios to temperature changes (Δ

temperature) that describe variations in the temperature of the ocean from which the ice was originally evaporated. Use Excel to do this and work up a new column. Type “delta temp” in the first row of your new column and “(deg C)” in the second row. Now use Excel to calculate the Δ temperatures, filing your new column (use the Excel help menu if you do not know how to do this). Highlight the column and give the numbers two decimal places. Use the following relationship:

Type “= (C3 + 440) / 6.2” into the first cell, then put the cursor on the lower right corner of the cell until it turns into a cross. Click and hold the left mouse button and drag down to the end of the column. The cursor applies the relationship of the first cell to other cells.

Save your work. Think about why the Δ temperatures change with deuterium isotope ratio in the way they do.

Plot the Δ temperature curve as a function of ice age (use either a line or scatter plot)

and incorporate into your report. [5 points]

Questions 2. By how many degrees has climate varied in the past, as indicated by these data? [1

point] 3. Approximately when were the last glacial and interglacial periods? Within the most

recent glacial period, what were the highest and lowest Δ temperatures? What do you think Grand Forks might have looked like during these times? [3 points]

Part 3. The Atmospheric Composition and Dust Record

Use the following scatter plots of CO2 and CH4 concentrations, as well as Δ temperature and dust as a function of (ice) age, to answer the questions for this section. These were made from the same data you are using, and you may want to replicate them yourself to get more practice with Excel. Note: for plotting Δ temp on your graph, place that data on the “secondary axis.” [no points awarded, but I encourage you to make them nevertheless]

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CO2 & CH4 Concentrations, Plotted with Δ Temperatures

0

100

200

300

400

500

600

700

800

1 14 27 40 53 66 79 92 105 118 131 144 157 170 183


-12.00

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-8.00

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CO2 ppmvCH4 ppbvΔ Temp (deg C)

Dust & Temperature as a Function of Age

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200

300

400

500

600

700

800

1 15 29 43 57 71 85 99 113127141155169183


Dust

Con

cent

ratio

n S

cale

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dust 10-9cm3g-1Δ Temp (deg C)

Questions 4. Note the time of the two major warming events. Then look at how CO2 and CH4

change during the same time. From the data provided in this lab, can you tell which changes first, temperature or greenhouse gas (CO2, CH4) composition? Suggest reasons why it could work either way. [2 points]

17

5. These graphs do not show recent values. Think of several reasons why CO2, CH4,

and dust concentrations were different during glacial time as compared to the 18th century, and predict how the Industrial Revolution might have affected the global concentration of CO2 and CH4. [2 point]

Part 4. What Does All This Tell Us About Climate Today?

First, add another column to your Excel file to estimate the temperature at Vostok. Label this column Vostok Temp. (deg C). To do this, simply subtract 55.5 degrees from the values in the Δ temperature column to get an estimate of the temperature at Vostok itself.

Create scatter plots (without connecting lines) of CO2 vs. temperature and CH4 vs.

temperature using the Vostok data. Note: again for plotting Δ temp on your graph, place that data on the “secondary axis.” Next, use the Insert a linear “trend line” and report the equation and r2 value by checking those boxes in the option menu for trend lines of each scatter plot in your lab report. [3 points each] Questions 6. Why is the r2 value for CO2 or CH4 less than one? [1 point] Extra Credit Predict the temperature of Vostok today. Use today’s CO2 concentration (360 ppmv) to solve the linear regression equation from the past relationship between CO2 and temperature. How does this calculated temperature differ from the surface temperature today at Vostok? Explain why these might be different. [3 points] Additional Readings Monnin, E., A. Indermühle, A. Dällenbach, J. Flückiger, B. Stauffer, and T. F. Stocker. 2001. Atmospheric CO2 concentrations over the last glacial termination. Science, 291: 112-114. Petit, J. R., J. Jouzel, D. Raynaud, N. I. Barkov, J. M. Barnola, I. Basile, M. Bender, J. Chappellaz, J. Davis, G. Delaygue, M. Delmotte, V. M. Kotlyakov, M. Legrand, V. Lipenkov, C. Lorius, L. Pépin, C. Ritz, E. Saltzman, and M. Stievenard. 1999. Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica. Nature, 399: 429-436.

18

APPENDIX 3



Capstone Project




Final Paper:


You must include the following in your paper: 1. A review of the background issues, including a statement of need. 2. A discussion of the objectives of your project with a clear rationale for choosing these

objectives. 3. A clear statement and rationale for your choice of target audience(s). Why these folks? 4. What key questions did you have about your audience(s) and what information did you

gather about your target audience? How did you gather it? What are the strengths and limitations of what you know about them?

5. Clear presentation of your communication strategies. What principles of communication

are you recommending and why? 6. Specific examples - this should include central messages, possible examples of print or

other media. 7. Delineation of how the plan will be evaluated.

19

8. Recommendations: how the client can use this information; how future students may build on your work.



References must follow the publication style of the Professional Communication Style

(http://www.ieeepcs.org/activities_publications_transactions_authors.php). Any source which appears in the text must appear in the bibliography.



Personal Statement:



1. Students are expected to take primary responsibility for the development of their

capstone projects. You are expected to conceptualize, carry out, and report your projects. I suggest you formulate your project to help you in your academic career (e.g. thesis chapter, published paper, etc.).



20



21

APPENDIX 4



LAB 1: RESEARCH ON THE MIND

1. The Scientific Method ………………………………………………………… 1 2. Starting a Research Project ………………………………………….........… 6 3. Reporting Scientific Work ……………………………………………...…….. 8 4. The Oral Presentation ………………………………………..…………..…. 10 5. Group Communications …………………………..…………………...……. 12 1. The Scientific Method

Science is best defined as a careful, disciplined, logical search for knowledge about any and all aspects of the universe, obtained by examination of the best available evidence and always subject to correction and improvement upon discovery of better evidence. What's left is magic. And it doesn't work.

-- James Randi The scientific method helps us create research that is quantifiable (measured in

some fashion), verifiable (others can substantiate our findings), replicable (others can repeat the study), and defensible (provides results that are credible to others--this does not mean others have to agree with the results). The scientific method is often used in everyday life and should be evident in any research report, paper, or published manuscript.

Corollaries among the Scientific Method, Common Sense, and Paper Format

Scientific Model Common Sense Paper Format Research Question Why Intro Develop a theory Your answer Intro Identify variables How Method Identify hypotheses Expectations Method Test the hypotheses Collect/analyze

data Results

Evaluate the results What it means Conclusion Critical review What it doesn’t

mean Conclusion

1.1. Scientific Method: The Steps

22

Observatio Predictions

not consistent-

modify hypothesis

Hypothesis

Consistent

Theory

TESTS

The scientific method is the best way yet discovered for winnowing the truth from lies and delusion.

1. Observe some aspect of the universe. 2. Invent a tentative description, a hypothesis that is consistent with what you have

observed. 3. Use the hypothesis to make predictions. 4. Test those predictions by experiments or further observations and modify the

hypothesis in the light of your results. 5. Repeat steps 3 and 4 until there are no discrepancies between theory and

experiment and/or observation.

When consistency is obtained the hypothesis becomes a theory and provides a coherent set of propositions which explain a class of phenomena. A theory is then a framework within which observations are explained and predictions are made.

Figure 1. Scientific method flow diagram. The great advantage of the scientific method is that it is unprejudiced (mostly): you

do not have to believe a given researcher; you can redo the experiment and determine whether his/her results are true or false. The conclusions will hold irrespective of the state of mind, or the religious persuasion, or the state of consciousness of the investigator and/or the subject of the investigation. Faith, defined as belief that does not rest on logical proof or material evidence, does not determine whether a scientific theory is adopted or discarded.

23

Watch out for anecdotes. – Beware of studies or statements that are based on extremely small sample sizes, especially those based on a sample size of 1. For example, if the conclusion of an analysis relies on the statement from one individual, one measurement, or one observation, then be careful with conclusions being drawn. This sort of data may make for interesting stories, but the results alone are NOT scientific, and no conclusions should be based on them. Further work is required. A theory is accepted not based on the prestige or convincing powers of the

proponent, but on the results obtained through observations and/or experiments which anyone can reproduce: the results obtained using the scientific method are repeatable. In fact, most experiments and observations are repeated many times (certain experiments are not repeated independently but are repeated as parts of other experiments). If the original claims are not verified, the origin of such discrepancies is hunted down and exhaustively studied.

In some cases, depending on the nature of the questions, we cannot perform

experiments; all information is obtained from observations and measurements. Theories are then devised by extracting some regularity in the observations and coding this into physical laws.

There is a very important characteristic of a scientific theory or hypothesis which

differentiates it from, for example, an act of faith: a theory must be ``falsifiable.'' This means that there must be some experiment or possible discovery that could prove the theory untrue. For example, Einstein's theory of Relativity made predictions about the results of experiments. These experiments could have produced results that contradicted Einstein, so the theory was (and still is) falsifiable.

In contrast, the theory that ``the moon is populated by little green men who can read

our minds and will hide whenever anyone on Earth looks for them, and will flee into deep space whenever a spacecraft comes near'' is not falsifiable: these green men are designed so that no one can ever see them. On the other hand, the theory that there are no little green men on the moon is scientific: you can disprove it by catching one. Similar arguments apply to abominable snow-persons, UFOs, the Loch Ness Monster, etc.

A frequent criticism made of the scientific method is that it cannot accommodate

anything that has not been proved. The argument then points out that many things thought to be impossible in the past are now everyday realities. This criticism is based on a misinterpretation of the scientific method. When a hypothesis passes the test it is adopted as a theory it correctly explains a range of phenomena it can, at any time, be falsified by new experimental evidence. When exploring a new set or phenomena, scientists do use existing theories but, since this is a new area of investigation, it is always kept in mind that the old theories might fail to explain the new experiments and observations. In this case new hypotheses are devised and tested until a new theory emerges.

1.2. What is the difference between a fact, a theory and a hypothesis?

In popular usage, a theory is just a vague and fuzzy sort of fact and a hypothesis is often used as a fancy synonym to `guess'. But to a scientist a theory is a conceptual

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framework that explains existing observations and predicts new ones. For instance, suppose you see the Sunrise over the horizon. This is an existing observation which is explained by the theory of gravity proposed by Newton. This theory, in addition to explaining why we see the Sun move across the sky, also explains many other phenomena such as the path followed by the Sun as it moves (as seen from Earth) across the sky, the phases of the Moon, the phases of Venus, the tides, just to mention a few. You can today make a calculation and predict the position of the Sun, the phases of the Moon and Venus, the hour of maximal tide, all 200 years from now. The same theory is used to guide spacecraft all over the Solar System.

A hypothesis is a working assumption or an educated guess. Typically, a scientist

devises a hypothesis and then sees if it stands up to scrutiny by testing it against available data (obtained from previous experiments and observations). If the hypothesis does stand up to scrutiny after repeated testing, it is then considered to be a theory.

1.3. Occam’s Razor?

When a new set of facts requires the creation of a new theory, the process is far from the orderly picture often presented in books. Many hypotheses are proposed, studied, rejected. Researchers discuss their validity (sometimes quite heatedly) proposing experiments which will determine the validity of one or the other, exposing flaws in their least favorite ones, etc. Yet, even when the unfit hypotheses are discarded, several options may remain, in some cases making the exact same predictions, but having very different underlying assumptions. In order to choose among these possible theories a very useful tool is what is called Occam’s razor or the Principle of Parsimony.

Occam’s razor is the principle proposed by William of Occam in the fourteenth

century: ``Pluralitas non est ponenda sine necessitate,'' which translates as ``entities should not be multiplied unnecessarily.''

In many cases this is interpreted as ``keep it simple'', but in reality the Razor has a

more subtle and interesting meaning. Suppose that you have two competing theories which describe the same system, if these theories have different predictions then it is a relatively simple matter to find which one is better: one does experiments with the required sensitivity and determines which one give the most accurate predictions. For example, in Copernicus' theory of the solar system the planets move in circles around the sun, in Kepler's theory they move in ellipses. By measuring carefully the path of the planets it was determined that they move on ellipses, and Copernicus' theory was then replaced by Kepler's.

But there are theories which have the very same predictions and it is here that the

Razor is useful. Consider form example the following two theories aimed at describing the motions of the planets around the sun:

1. The planets move around the sun in ellipses because there is a force between any of

them and the sun which decreases as the square of the distance. 2. The planets move around the sun in ellipses because there is a force between any of

them and the sun which decreases as the square of the distance. This force is generated by the will of some powerful aliens.

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Since the force between the planets and the sun determines the motion of the former and both theories posit the same type of force, the predicted motion of the planets will be identical for both theories. The second theory, however, has additional baggage (the will of the aliens) which is unnecessary for the description of the system.

If one accepts the second theory solely on the basis that it predicts correctly the motion of the planets one has also accepted the existence of aliens whose will affect the behavior of things, despite the fact that the presence or absence of such beings is irrelevant to planetary motion (the only relevant item is the type of force). In this instance Occam’s razor would unequivocally reject the second theory. By rejecting these types of additional irrelevant hypotheses, you are guarding against the use of solid scientific results (such as the prediction of planetary motion) to justify unrelated statements (such as the existence of the aliens), which may have dramatic consequences. In this case the consequence is that the way planets move, the reason we fall to the ground when we trip, etc. is due to some powerful alien intellect, that this intellect permeates our whole solar system, it is with us even now...and from here an infinite number of paranoid derivations.

For all we know the solar system is permeated by an alien intellect, but the motion of the planets, which can be explained by the simple idea that there is a force between them and the sun, provides no evidence of the aliens' presence nor proves their absence.

When we are face with two theories which have the same predictions and the available data cannot distinguish between them, the Razor directs us to study in depth the simplest of the theories. It does not guarantee that the simplest theory will be correct, it merely establishes priorities.

A related rule, which can be used to slice open conspiracy theories, is Hanlon's

Razor: ``Never attribute to malice that which can be adequately explained by stupidity.''

The objective of science is to explain reality in such a fashion so that others may develop their own conclusions based on the evidence presented. To do this, scientists use the scientific method to as a systematic approach to understanding the world around us that employs specific rules of inquiry. 2. Starting a Research Project

Before starting a research project you should devise a plan to make sure you use your time efficiently. Here are some things you should consider when planning your research:

1. How long do you have to conduct your research?

don't leave it to the last minute - plan your time! do you only have time to consult books and periodicals held in the Library, or do

you have time to order inter-library loans? do you have time to consult several databases for references or just one?

2. How much detail do you need?

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if you just need an overview of a topic then an encyclopedia or book might give you enough information

if you are starting a Ph.D. you will need to find all relevant publications

3. Think about your topic

what key words describe it? think about synonyms or other related terms - include them in your search what years do you need to cover? Temporal scale? is your research limited to one country or geographical region? Geographical

scale?

4. Learn how to search databases efficiently using Library guides

consult the ‘Articles Indexes and Databases’ of the UND Chester Fritz Library web page for help on building a search strategy

experiment with a search strategy with specific databases (e.g. Biological Abstracts)

use the online help screen provided by each database The Chester Fritz Library web site also contains links to many other valuable

references you may find useful. It also holds a number of books which include guidance on planning your research. Also, check out for detailed guidance in formulating a successful search strategy: http://www.lib.berkeley.edu/TeachingLib/Guides/Internet/Strategies.html

5. Develop a research question

The research question should be a clear statement about what you intend to

investigate. It should be specified before research is conducted and openly stated in reporting the results.

Your research question should be relevant and advance the field of study. You can only know this by conducting an extensive literature search and gaining knowledge of the current state of the field. NEVER assume that you know the current state of the field; it’s always changing.

One conventional approach is to put the research question in writing in the introduction of a report starting with the phrase "The purpose of this study is ..." This approach forces the researcher to:

o identify the research objective (allows others to benchmark how well the study

design answers the primary goal of the research) o identify key abstract concepts involved in the research

Research Question: Is the quality of public sector and private sector employees different?

Purpose statement: The purpose of this study is to determine if the quality of public and private sector employees is different.

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Abstract concepts: The starting point for measurement. Abstract concepts are best understood as general ideas in linguistic form that help us describe reality. They range from the simple (hot, long, heavy, fast) to the more difficult (responsive, effective, fair). Abstract concepts should be evident in the research question and/or purpose statement. An example of a research question is given below along with how it might be reflected in a purpose statement. In general, abstract concepts will need to be defined. Always be careful of presenters who rely on abstract concepts to illustrate a point.

6. Develop Hypothesis

A hypothesis is one or more propositions that suggest why an event or phenomenon occurs. It is our view or explanation for how the world works.

Hypotheses provide a framework for further analysis that are developed as a non-normative explanation for "What is" not "What should be."

A hypothesis should have logical integrity and include assumptions that are based on paradigms. These paradigms are the larger frame of contemporary understanding shared by the profession and/or scientific community and are part of the core set of assumptions from which we may be basing our inquiry.

7. Identify Variables

Variables are measurable abstract concepts that help us describe relationships. In the previous research question "Is the quality of public sector and private sector

employees different?" the key abstract concepts are employee quality and employment sector. To measure "quality" we need to identify and develop a measurable representation of employee quality. Possible quality variables could be performance on a standardized intelligence test, attendance, performance evaluations, etc. The variable for employment sector seems to be fairly self-evident, but a good researcher must be very clear on how they define and measure the concepts of public and private sector employment.

8. Many more specific steps… 3. Reporting Scientific Work

Science is a communal activity. Only as the entire community of interested scientists takes up new facts and hypotheses do these facts and hypotheses become part of science. Therefore, one of the major responsibilities of scientists is to see that their work is reported to all those who might be interested. Often this is done by word of mouth when scientists of similar interests gather together at meetings. But to be assured of a permanent place in the scientific edifice, the work is reported in a paper submitted to a scientific journal. In most cases, the paper will not be accepted for publication until several knowledgeable scientists from other laboratories who serve as referees have approved it. Often they will suggest editorial changes in the paper or even additional experiments that should be done before the paper is accepted for publication. Papers in science usually follow a standard plan. The paper is divided into several sections as follows.

3.1. Introduction.

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This section of the paper describes the scientific question or problem that was the subject of the investigation. The introduction also includes references to earlier reports of these and other scientists that have served as the foundation for the present work. 3.2. Materials and Methods.

Here are precisely described the materials used (e.g., strains of organism, source of the reagents) and all the methods followed. The goal of this section is to give all the details necessary for workers in other laboratories to be able to repeat the experiments exactly. When many complex procedures are involved, it is acceptable to refer to earlier papers describing these methods in greater detail.

3.3. Results.

Here the authors report what happened in their experiments. This report is usually supplemented with graphs, tables, and photographs.

3.4. Discussion.

Here the authors point out what they think is the significance of their findings. This is the place to show that the results are compatible with certain hypotheses and less compatible, or even incompatible, with others. If the results contradict the results of similar experiments in other laboratories, the discrepancies are noted here, and an attempt may be made to reconcile the differences.

3.5. Acknowledgments.

In this brief but important section, the authors give credit to those who have assisted them in the work. This usually includes technicians (who may have actually performed most of the experiments!) and other scientists who donated materials for the experiments and/or gave advice about them.

3.6. References.

This section gives a careful listing of all earlier scientific work referred to in the main body of the paper. Most of the references are to other scientific papers. Each reference should provide enough information so that another person can locate the document. This means that each reference should include the name(s) of the author(s), the journal or book in which the report appears, and the year of publication. In the case of scientific journals, the volume number in which the paper appears and the page number on which the paper begins should be included. Sometimes the full title is given as well, although scientific papers often have such long titles that this is omitted from the reference.

3.7. Summary or abstract.

This section includes only the essence of the other sections. It should be as brief as possible, telling the reader what the goal of the experiment was, what was found, and the significance of the findings. The abstract is often placed at the beginning of the paper rather than at its end.

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When a paper is written and rewritten and every coauthor has reviewed and revised it, you will reach a point where you just cannot see how to make it better. You have now reached the point where you ask for reviews from peers. These might be the most valuable types of reviews because your peers probably have a cursory and not an in-depth knowledge of your work. They will probably make suggestions about issues you have not thought of, or provide insight to issues you may have passed over. Once this is done and additional changes are made, you will probably be ready to submit the paper for publication (or grade).

Submitting a paper to a scientific journal requires that you first read the “Instructions

to Authors.” This information will probably tell you about page charges and submission requirements for page size, line spacing, and numbering, and other style issues. It is important to submit your paper to only one journal. You may think your chances for acceptance are better if you submit your paper to more than one journal. This is typically not allowed and considered unethical. Acceptance of your paper depends on not only how good the research and how well it is written, but also on the suitability of the subject and the acceptance rate of the journal.

4. The Oral Presentation

Nothing is worse for an audience member than to be forced to sit through a presentation that is poorly prepared and inadequately presented. Below is an outline of questions you should consider when preparing and presenting your presentation.

4.1 The Presentation

A. Introduction

1. Are your hypothesis and objectives clear for the audience? 2. Do you provide the audience with clear rationale and justification for

your study? 3. Does your introduction follow a logical pattern, and is it related to other

literature and scientific principles?

B. Materials and methods 1. Do your methods have the support of the literature and scientific

principles? 2. Do you show a logical, systematic process for executing the experiment

and collecting the data to carry out your objectives? 3. Do you make clear your use of appropriate experimental design and

statistical analyses?

C. Results and discussion 1. Do you summarize results (i.e. emphasize main points, as you begin

and end this section)? 2. Do you relate the results clearly to your objectives? 3. Do you carefully choose a limited number of data points to support your

contentions and present them in simple illustrations, graphs, tables, and lists?

4. Do you discuss your points in terms of:

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a. Their relation to other research. b. Their practical or scientific applications?

D. Conclusions 1. Do the conclusions reiterate main points for the audience to remember? 2. Do you show a list and clearly relate it to your objectives? 3. Do you give examples of application and use for your findings?

4.2 Visual aids

A. Number – Are there too many or too few slides for the time you have? B. Content

1. Are the slides clearly coordinated with your presentation? 2. Is the purpose of each slide readily apparent? 3. Do you have a balance of data, lists, and information slides with

photographs interspersed throughout? 4. Have you included all expected slides: title, list of objectives, and

conclusions?

C. Quality – Are your slides: 1. Neat and spaced to fill the screen? 2. Simple and free from excessive data? 3. Easy to comprehend (e.g. proper size print, good content, good design,

clearly labeled axes)? 4. Free from garish color or any other embellishment that could distract

from your message?

4.3 Speaker

A. Are you prepared? 1. Are you familiar with your speech and slides? 2. Will you and your audience be comfortable with your appearance?

B. To what extent do the following support or distract: 1. Mannerisms and gestures? 2. Audience contact (eye contact, and facial expressions)? 3. Voice, speech patterns, and ease in speaking? 4. Your attire, posture, and poise?

C. During your presentation, keep the following in mind: 1. Avoid reading from the slides or from notes. 2. Be sure your eye contact covers all the audience. 3. Put the pointer down when you’re not using it. This may not be

possible in all cases. 4. Don’t put your hands in your pockets. 5. Never apologize or make an excuse for a bad slide. A bad slide is

worse than no slide. 6. Keep your voice enthusiastic and loud enough. 7. Be sure to use enough but not too much time.

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5. Group Communications

Group communications are quickly becoming the status quo in educational, private industry, and research settings. As with individual efforts, preparation and competent execution are important to provide clear communication and prevent wasted time and effort. Selecting a format was well as preparing for and carrying out communication with a group depends to a large extent on whether and audience is involved.

5.1 Decision Making

Decision-making involves alternatives. Defining what the alternatives will likely require research and discussion. Making the best possible decision can depend on gathering information and even solving problem along the way. But after discussion, the group should reach a consensus or conduct a vote to make a final decision.

5.2 Problem Solving

Example problem solving procedure: A. The problem is clearly defined and objectives are set out and understood by

all members of the group. B. Members of the group plan their individual and collective actions. They may

divide responsibilities for gathering information and offering opinions. C. As individuals and as a group, they devise a plan of action. D. They act on the plan and analyze outcomes. E. They evaluate the results if their actions and determine whether the solution

was acceptable.

Additional web references: http://methods.fullerton.edu/framesindex.html THIS WEEK’S LAB ASSIGNMENT: Questions (1 pt. each): 1) Science is:

(a) absolute, (b) mystical, (c) testable, (d) unpredictable

2) Scientific results must be verified by: (a) constructing plausible theories, (b) consulting noted scientific authorities, (c) experiments, (d) government agencies

3) A hypothesis is:

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(a) a guess based on observations, (b) a process of experimentation, (c) an Italian building, (d) the truth

4) What would scientists do to test a hypothesis? (a) ask questions, (b) create an experiment, (c) make observations, (d) none of the above

Longer questions (8 pts. each): 5) Cold Fusion. It was touted as the answer to the world's energy problems: A pair of

researchers from the University of Utah announced in 1989 that they had achieved fusion with a simple apparatus at room temperature. Fusion is the joining of two nuclei to form a larger nucleus. If unstable, the nucleus will break apart and release energy. The generally acceptable methods of fusion involve extremely high temperatures or particle accelerators--dangerous and expensive methods. The discovery of a reliable cold fusion method had the potential of supplying cheap energy to the world. If you were asked about the validity of cold fusion, what would you say?

6) The Roswell Crash. Is Agent Mulder right? Are there Men In Black? Did a UFO

crash in Roswell, N.M., in 1947? A good proportion of people think the latter happened – according to a 1997 Gallup poll, 80% of Americans have heard of the Roswell incident and 31% believe it's true. In 1947 a rancher found debris which he thought could be from a flying saucer. After a few days of investigation, it was declared to be from weather balloons and for several decades the incident was closed. About 30 years later a UFO researcher started interviewing hundreds of "witnesses" to the crash – witnesses who for some reason kept quiet for 3 decades, who occasionally changed their stories, and sometimes told outright lies. Rumors of a government cover-up and alien bodies abounded, including a Fox-TV special Alien Autopsy. As circumstances sometimes have it, you are asked about the scientific validity of the Roswell Crash. How do you respond?

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APPENDIX 5



LAB 3: GLOBAL TEMPERATURE CHANGE 1. Introduction10

An overall increase in global-mean atmospheric temperatures is predicted to occur in response to human-induced increases in atmospheric concentrations of heat-trapping ''greenhouse gases”. The most prominent of these gases, carbon dioxide, has increased in concentration by over 30% during the past 200 years, and is expected to continue to increase well into the future. Other changes in atmospheric composition complicate the picture. In particular, increases in the number of small particles (called aerosols) in the atmosphere regionally offset and mask the greenhouse effect, and stratospheric ozone depletion contributes to cooling of the upper troposphere and stratosphere.

Source: Source: http://www.giss.nasa.gov/

Many in the scientific community believe that a distinctive greenhouse-warming

signature is evident in surface temperature data for the past few decades. Some, however, are puzzled by the fact that satellite temperature measurements indicate little, if any, warming of the lower to mid-troposphere (the layer extending from the surface up to about 8 km) since such satellite observations first became operational in 1979. The satellite measurements appear to be substantiated by independent trend estimates for this period based on radiosonde data. Some have interpreted this apparent discrepancy between surface and upper air observations as casting doubt on the overall reliability of the surface temperature record, whereas others have concluded that the satellite data (or the algorithms that are being used to convert them into temperatures) must be erroneous. It is also conceivable that temperatures at the earth's surface and aloft have not tracked each other

10 Modified from Reconciling Observations of Global Temperature Change, 2000, Commission on Geosciences, Environment and Resources, National Academy of Sciences, USA

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perfectly because they have responded differently to natural and/or human-induced climate forcing during this particular 20-year period. Whether these differing temperature trends can be reconciled has an implication for assessing how much the earth has warmed during the past few decades and for potential future temperature trends.

In this lab, you will explore potential global temperature change across different

continents and time periods, and also look at methane and carbon dioxide in the atmosphere. You will initially work alone, but then share your data with the others in the class in order to complete the assignment.

LAB ASSIGNMENT Part 1. Temperature Data Preparation

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Temperature records for various weather stations around the world are available from the NASA Goddard Institute for Space Studies (GISS) (http://www.giss.nasa.gov/data/update/gistemp/station_data/). Each student will select an area to analyze according to the following table.

Name Your Area To Examine Africa Asia Europe North America South America Australia

Go to the website listed above and choose which part of the continent you will

explore. Click that spot on the NASA GISS Surface Temperature website. This should bring up a list of localities with temperature records. Select a locality from this list. Make sure that your site has a reasonably long and continuous record of measurement. Once you have a site selected, click on the “Click for monthly data in table form.” From this raw data, save this page on your hard drive as a text file (not as a webpage). Do not forget where you saved your file and what you called it.

Using Excel, open the saved text file. You will be prompted for information on how to

import this file. You should select: Original Data Type-Delimited; Delimiters-Tab and Space; and Column Data Format-General. After selecting these options, click finish to have your data page. Save this page as an Excel file. Again, do not forget where you saved your file and what you called it. In your data, gaps in the data are registered as “999.9.” If you leave these as they are, your analyses will be highly skewed. Therefore, remove these numbers from the spreadsheet, leaving only blank cells.

Now, compare January, April, July, and October temperature (scatter plots). If you

are not sure how to do this, refer to last week’s lab for specific instructions. Next, use the Insert a linear “trend line” and report the equation and r2 value by checking those boxes in the option menu for trend lines of each scatter plot in your lab report.

Part 2. Greenhouse Gases and the Temperature Record

From your data above, produce a graph that shows annual temperature average by year (scatter plot with connecting line). Add a trendline and report the equation and r2 value and include in your report. Next, you will add CO2 and CH4 data to your current spreadsheet. To do this, go to Public Drive/ESSP_Public/Biogeochemical Block/Lab-Temperature Change…/ch4.xls (for methane data) and co2.xls (for CO2 data). Open each of these files and select those cells of TOTAL CH4 that correspond to the earliest year of temperature record from your site. For example, CH4 data begins with 1860, but your temperature record may begin in 1945. Select the CH4 cells between 1945 and the last year of temperature data. Copy these cells and paste them in the appropriate place (i.e. corresponds to the correct sequence of years) in your temperature data sheet. Do the same for the CO2 data.

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Now, produce a graph that shows annual temperature average by year for your site and CH4 and CO2. Refer to last week’s lab for hints on how to do this if you are not sure. Add a trend line to each of the variables and include with your report.

Assignment Write a short essay (≤2 pages) describing the changes in temperature at your site noting the magnitude of the change, variations over time, and what consistency, if any, was observed between localities. Address what role, if any, CO2 and/or CH4 may play in any observed temperature change. Be sure to address:

How large was the change in temperature at your site and how consistent was it from month to month?

How consistent were the changes observed among other localities? Do you think the temperature trends you observe in your data reflect a significant

change in climate over time? Why or why not? What role, if any, do CO2 and/or CH4 play in any observed temperature change?

Grading will be based on the following criteria: spelling and grammar (2 pts.), logical argument and clarity (10 pts.), structure and flow of writing (3 pts.), proper formatting and inclusion of graphs (10 pts.).

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APPENDIX 6



Select an environmental-related text to examine. This may be a brochure, flyer, advertisement, advisory, newspaper or magazine article, etc. You will provide a written paper and lead a class discussion that examines the following:

What message(s) is the text attempting to communicate? Can you identify the intent of the text? Who or what is the target audience of the text?

Using the Jacobson model of communication, what assumptions is the sender

making about the receiver?

What messages (if any) does it communicate about nature or ecosystems?

What techniques or strategies does it use?

In your estimation, how effective is it?

Include anything else you find interesting to discuss. Make references to class readings as appropriate.

The written portion of this assignment should not exceed five pages of text (or 10 pages with pictures, figures, etc.). The discussion portion should be targeted to about 30 minutes.

This assignment will be due on September 6th. Your presentation will also be on that

day.

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APPENDIX 7



LAB 3: PREDICTIVE SPATIAL MODELING OF SPECIES’ DISTRIBUTIONS 1. Introduction

New computational and GIS technologies provide innovative opportunities to use species locality data to create predictive spatial models and maps of species distributions. One technique of considerable interest, ecological niche modeling, uses primary locality data to discover the association between a species’ geographical occurrence and the environmental dimensions that may determine its geographic distribution. This approach produces an approximation of a species’ fundamental ecological niche, which provides a basis for understanding numerous ecological and geographic phenomena related to its distribution. This approach also produces a model for predicting what a species’ geographical distribution might become, avoids numerous problems associated with sampling bias, and has excellent overall predictive abilities. One way it avoids sampling bias is by identifying a species’ ecological niche without a complete or balanced sample of the species’ geographic distribution.

2. Ecological Niche Modeling

We will use the Genetic Algorithm for Rule-Set Prediction (GARP)11, an iterative, artificial intelligence approach that includes several distinct algorithms (e.g. BIOCLIM, logistic regression). GARP is a software package for biodiversity and ecological research that allows the user to predict and analyze wild species distributions. GARP is a genetic algorithm that creates ecological niche models for species. The models describe environmental conditions (abiotic primarily) under which the species should be able to maintain populations.

For input, GARP uses a set of point localities where the species is known to occur

and a set of geographic layers representing the environmental parameters that might limit the species' capabilities to survive. GARP searches iteratively for non-random correlations between species presence and absence and environmental parameter values using several different types of rules. Each rule type implements a different method for building species prediction models. Currently there are four types of rules implemented: atomic, logistic regression, bioclimatic envelope, and negated bioclimatic envelope rules. For a comprehensive description of GARP algorithm, please read the GARP Technical Manual and Users Guide (http://biodi.sdsc.edu/Doc/GARP/Manual/manual.html). 3. Getting Started 11 Desktop GARP 1.1.3. http://www.lifemapper.org/desktopgarp/

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3.1. The GARP Interface The GARP user interface is relatively simple. It contains just one window where the user specifies all the parameters and data to be used in the experiment. Below is a sample of the interface.

Below is a detailed functional description of each user interface panel. The Species Data Points panel handles the species occurrence (point) data. A sample of this area is shown below.

New species occurrence information can be entered by clicking the Upload Data Points button. It will open a dialog box to specify the location of the occurence data file. Currently three formats are supported: Comma delimited, MS Excel Spreadsheets and ArcView Shapefiles.

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Comma delimited and Excel files should contain three columns: the first one for species name, the second for longitude, and the third for latitude. The first line is ignored, so it can be used for labels.

In this version, GARP accepts only files in this format, so make sure the columns are

ordered: species name, longitude and latitude. Notice that longitude comes before latitude. Each line of the file represents a single data point entry for the species. Data points

for the same species must come together. Different species names define different species for the software. Below is a sample Excel worksheet and the corresponding comma delimited file containing species information for two species. The actual files can be downloaded at MS Excel sample and comma delimited sample.

3.2. Optimization Parameters

On the Optimization Parameters panel, the user can specify some parameters that control the overall behavior of the genetic algorithm. A sample of this panel is shown below.

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The number of runs per experiment defines how many times each distinct task will be performed within the experiment. For example, for two species and 10 runs per experiment, 20 runs in that experiment will be executed: 10 for the first species and 10 for the second one.

The convergence limit establishes a stop condition for iterations within the genetic algorithm. Its behavior varies depending on how difficult or easy the problem is. Usual values are between 0.01 and 0.10. If this parameter is set to 0, the algorithm will stop only when the maximum number of iterations is reached.

Max iterations value establishes another stop condition for the genetic algorithm. It forces the optimization to stop at the specified iteration, even if the convergence limit has not been reached yet. More iterations tend to yield more stable results. Usual values are between 100 and 1000.

The rule type checkboxes allow the user to specify which algorithm is used to

produce rules in the species model. For this assignment, you will use all of the rules. The all combinations checkbox generates one task for each combination of the

checked rules. For example, if range, logit and atomic rules are checked, GARP will create tasks where only each of those rules are used, then one for range and logit rules, one for range and atomic rules, one for logit and atomic rules, and one for all three rules combined. This is useful for analyzing the impact of each particular rule on the results. The labels below the checkbox show how many combinations will be created and also the total tasks or runs that will be executed (combinations times runs).

Unless otherwise stated, you will use the default settings in the Optimization

Parameters section of GARP.

3.3. Environmental Parameters

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The Environmental Layers panel allow the user to define the environmental coverages that will be used as input for the prediction. The algorithm will try to correlate the input data points to the values on those layers to get the final prediction. The dataset combo box displays the choices for the dataset that will be used on the experiment. The datasets listed on this combo box are the ones scanned using the menu option Datasets->Scan directory.... Once the dataset has been chosen, GARP will automatically list all layers present on that dataset on the layers to be used list box. There, the user can control which layers will be used by clicking on the checkbox that appears to the left of each layer name.

Below the layers list, there are three radio buttons that define how the selected layers

will be used. The first one, all selected layers, will force GARP to use all selected layers in the optimization. All combinations of selected layers will cause the experiment to have one task for each possible combination of the selected layers. The all combinations of selected size N radio button has similar effect, but will limit the experiment to the combinations that contains exactly N layers. The last two alternatives using combinations of layers are useful for determining which layers are important to a species. A method for analyzing that would be using linear multiple regression to predict the error values (omission and commission), using the information on whether a particular layer was used on a task as an independent variable.

Note: The use of combinations of layers may cause the number of tasks within the

experiment to be too large. There is a label next to the bottom of the panel that shows how many combinations that setup will yield. Tests have shown that GARP can handle well up to 10,000 tasks in the same experiment. 3.4. Output Parameters

The Output panel specifies the output prediction map format and the output directory for maps and other generated documents.

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The prediction maps can be generated in three formats:

• bitmaps: MS Windows bitmaps, with extension ".bmp"; • ASCII raster grids: ASCII text format, with extension ".asc"; • ESRI Arc/Info grids: ESRI proprietary format for grid spatial data storage and

management. A separate directory is created for each grid.

Another important file that is stored on the output directory is the file result.xls which stores a summary of all tasks, error messages, result parameters, statistical tests, accuracy, and more.

All .bmp, .asc and other result files are stored under the directory specified on the

text field Output directory. This must be a valid folder (local or remote) accessible through the computer being used. ESRI Arc/Info grids are stored in subdirectories of the Output directory and called sequentially grid00000, grid00100, grid00200 and so on. The directory grid00100 for example, stores all grids resulting from tasks 100 through 199. This is because of an ESRI limitation on the number of grids allowed in a directory.

3.5. Visualizing Results

Import each grid into ArcMap to visualize. I will provide detailed methodology how to do this during the lab. Please be prepared to take notes.

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LAB ASSIGNMENT In this lab, you will use GARP to produce predictive geographical maps of species’ distributions over landscapes. Specifically, you are to do: (1) Produce four predictive distributional map for two species. The locality data for these

species will be provided to you. For each species, I want a world-wide analysis and a North American analysis using the “Best Subsets” setting. Print these maps out keeping in mind last week’s Lab and qualities of good maps. (14 pts.).

(2) Produce a map at the continental scale not using the “Best Subset” option. You will use

the same data from #1; you choose the species. Print out and provide a brief explanation as why these two differ. (3 pts.)

(3) Provide three uses that maps produced using GARP might be used for (e.g. identifying

areas that should be conserved). (3 pts.). Further Readings Anderson, R. P., D. Lew, and A. T. Peterson. 2003. Evaluating predictive models of

species' distributions: criteria for selecting optimal models. Ecological Modelling 162: 211-232.

Peterson, A. T., J. Soberón, and V. Sánchez-Cordero. 1999. Conservatism of ecological

niches in evolutionary time. Science 285: 1265-1267. Peterson, A. T., M. A. Ortega-Huerta, J. Bartley, V. Sánchez-Cordero, J. Soberón, R. H.

Buddemeier, and D. R. B. Stockwell. 2002. Future projections for Mexican faunas under global climate change scenarios. Nature 416: 626-629.

Sánchez-Cordero, V., and E. Martinez-Meyer. 2000. Museum specimen data predict crop

damage by tropical rodents. Proceedings of the National Academy of Sciences USA 97: 7074-7077.

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APPENDIX 8



Micro-Economics of Bottled Water Simple Homework: 1) Use the daily water use data determined on Wednesday along with GF price info and determine what your daily average water use costs on average. 2) Figure out how many 8 oz. glasses of tap water you could have for the price of a Clifford Hall vending machine bottle of 12 oz. Desani (Coca-cola) water. Hard Homework: 3) Thinking about your answer to Q2, justify, in purely economic terms, why you would ever buy bottled water (think about all the reasons you buy bottled water as well as why others might) – if you have honestly never purchased bottled water, than (if you want) explain why.

4) Describe, in as many ways as you can, how this issue of bottled water is linked with the other cycles covered in 501 & 502 (no more than two pages).

This is funny because it essentially depicts what Coca-cola does to produce Desani the nations # 1 bottled water product.

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APPENDIX 9 Department of Earth System Science and Policy ESSP 502, Spring 2005 502 Block I: Material Cycling Full Cost Accounting Analysis of hypothetical landfill

Landfills have many types of “impacts”, including biophysical impacts such as contamination of groundwater and socio-economic impacts such as those on property values or potential health risks. The first problem we encounter is therefore how to decide which potential impacts to include in an analysis and which to exclude. Many analyses of the “costs” of landfilling consider only the obvious, direct costs, such as land purchase, construction costs, and supplies and labor for operation and management. It can be argued that such an approach significantly underestimates the true costs of a landfill project. We know that landfills have the potential to create serious impacts on the built and natural environment, and on people who are part of those environments. Yet these impacts are almost always excluded from, for instance, a cost benefit analysis of waste management alternatives.

Today’s assignment is to perform a Full Cost Accounting Assessment of a hypothetical landfill project.

Using the data provided below in Tables 1-3 found on page 3, your task is to calculate a “truer”(more complete) cost of this hypothetical landfill project.

Calculating the true costs of a landfill project demands the use of several different tools. The simple approach is to break the task into several steps.

1) Calculate the capital costs 2) Calculate the operating costs 3) Calculate the potential “opportunity costs” of the land 4) Calculate the costs of close-out 5) Calculate the costs of property-value impacts 6) Estimate the costs of other environmental impacts

Below is a little step-by-step process you are required to follow (HINT – it will be useful to create a cash flow table which includes: cost item, cost, timing, discounting formula) 1) Calculate the capital costs

The first and perhaps the simplest task is to calculate the costs of building the landfill. This step comprises several discrete calculations:

1) Calculate the total volume of the landfill. 2) Calculate the portion of that volume that is usable for waste disposal (as compared to

soil cover) = the volume of waste that the landfill can receive. 3) Calculate the mass of waste that the landfill can receive, from the known volume and

estimated waste density. 4) Calculate the costs of buying the land for the site. 5) Calculate the costs of excavation.

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6) Calculate the cost of a liner system, which will comprise four layers: a clay liner, a synthetic liner, a geo-textile layer, and a drainage net. Use unit costs and known landfill volume.

7) Add the costs of a lift station and a leachate collection and treatment system. 8) Total these costs.

2) Calculate the operating costs Operation and maintenance costs are typically much lower and less variable than one-time costs like construction. Assuming that the costs of hauling wastes are common to any waste disposal option, we can omit them from further consideration. Other operating costs can be calculated as follows:

1) Calculate the costs of covering waste with soil. 2) Calculate the volume of leachate generated (rainfall/yr*area*proportion of rainfall that

yields leachate). 3) Calculate the costs of leachate treatment. 4) Calculate the costs of generating gases from the landfill. In this case the city

proposes to construct gas collection equipment as part of the landfill design, so there is no additional cost related to gas generation.

5) Calculate the costs of any labor required (assume filling and treatment costs are included in the unit costs given). To simplify, ignore management costs.

3) Calculate the potential “opportunity costs” of the land Assume that the land base in this example is productive agricultural land. How would you figure out the agricultural opportunity cost? What is an appropriate time scale? 4) Calculate the costs of close-out The costs of close-out, or decommissioning, are hard to estimate with accuracy, simply because we cannot guess what environmental or regulatory conditions may prevail when the landfill is full. An estimate of 5% of total capital (construction) costs is not unrealistic for site closure. Another 2% or so of construction costs should likely be allocated for ongoing site management and monitoring after closure. – These costs could go on indefinitely – you decide. 5) Calculate the costs of property-value impacts Once the routine costs of construction and operation have been calculated, it should be possible to move onto less traditional cost areas. Among these, and often foremost in the minds of site neighbors, are property value impacts. We can never estimate these costs with certainty, but we can work from empirical evidence available in the literature, such as those produced by Hirshfeld et al., (1992). We would simply calculate the number of neighboring homes, their distance from the site, and the probable depreciation in their property values, and sum those costs. - - Are these onetime costs? You decide. Table 1. Basic Assumptions, proposed landfill project. Total land area available 304 ha

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Fill area 81 ha Average Depth of fill 15 meters Depth of clay liner 0.6 m Volume of cover 20% of total volume In-place refuse density 590 kg/cubic meter Land cost

Potential Opportunity Costs Agricultural rent

$24,700/ha $247/ha

Excavation cost $6,175/ha Cost of routine landfill cover $6,175/ha Average annual rainfall 102 cm Leachate/precip ratio 0.4 Rate of filling 682 t/day Estimated landfill life span ? – you tell me. Period of public ownership following close-out 60 years Rate of land appreciation 4% annually Annual property tax rate $1.50/$100 assessed value Typical value of residences within 5k of site $70,000 Source: Hirshfeld et al., 1992 Table 2. Estimated unit costs for key project components. Clay liner $5.23/ m3 Synthetic liner $0.11/mil-square meter Geotextile $0.16/ m2 Drainage net $0.27/ m2 Lift (pumping) station $30,000 each On-site pretreatment Construction Operation

$150,000 $0.001/ liter

Leachate hauling and treatment $0.008/ liter Source: Hirshfeld et al., 1992 Distribution of residences around the site It is possible to estimate the number of homes located within 0.5 km, within 0.5 to 1 km, and within 1 to 5 m. Their distribution is approximately as follows: Table 3. Distribution of residences around proposed landfill site Distance from site boundary (km)

Relative location Within 0.5 0.5 to 1 1 to 5 West 99 55 1 South 17 12 15 East 54 127 83 North 5 6 46 Total 175 200 145 Source: Hirshfeld et al., 1992 Property values are known to depreciate more quickly closer to a landfill site. Work by Hirshfeld et al. (1992) suggests that $70,000 homes within 0.5 km of a landfill depreciate on average about $18,000 after the landfill is sited; those between 0.5 to 1 km from the site depreciate by about $15,000; and those between 1 and 5 km depreciate by about $7,000.

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Below is a discounting decision tree that may be useful in calculating some of the costs. Discounting Formula

Source: Klemperer, W.D. 1996. Forest Resource Economics and Finance. McGraw-Hill Series in Forest Resources. Mcgraw-Hill Inc. 552 p. Estimate (in this assignment “Qualify”) the costs of other environmental impacts The “costs” of other environmental impacts are very difficult to estimate, and will likely be subject to considerable public debate. This, however, doesn’t mean that such estimates are not worth preparing or including in an analysis. Rather, it means that the analyst must make very clear what assumptions underlie the analysis and the methods used to estimate “costs”.

Identify the probable impacts

People identify environmental impacts in different ways - this , in fact is the crux of the debate on environmental impact assessment. Some common approaches include subjective assessment (in which the analyst simply lists the impacts that he or she believes are important: a risky process because it inherently reflects the interests and biases of the analyst); and matrix analysis, in which the analyst uses one of several types of matrix to organize information about project activities and their impacts. While matrix analysis is still very subjective, it is often more comprehensive than simply “eyeballing” a situation. Its clear

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organization can also assist the analyst in seeking additional viewpoints from external stakeholders. The most common form of an environmental impact assessment matrix is one like the following example, where project activities are listed down the vertical axis and environmental components are listed across the horizontal axis. The resulting matrix can be filled with information about the direction and magnitude of expected impacts. Even though this analysis is necessarily general and simplified, if completed for a detailed list of probable areas and severity of impact. NOTE: This type of study is what leads to more comprehensive (and less subjective) economic assessments of individual components. Many of you were introduced to techniques used in non-market valuation of environmental goods and services (and losses thereof due to damage) such as contingent valuation. For this assignment we will leave the quantification for another day, instead we will deal only with the qualification of potential values.

For this assignment create a matrix similar to the one above (you may change its format if you wish – that is add whatever dimensions you think should be there). Key point: In this case use the location of Manvel, ND to guide your assessments and assumptions. Fill in the “direction” of impact. If you wish you may put in an estimated magnitude on either a 10 point scale or a 0 to 1 scale. Precision such as that given in the example is not required – though if you’re interested in knowing how such precision can be estimated, the likely technique is called a Delphi analysis and I would be more than happy to explain it to you. Final Analysis:

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When you have determined the capital costs, the long-term operating and maintenance costs, and some examples of socio-economic costs (e.g. real estate depreciation, opportunity costs): Sum all costs and express on a per tonne basis as follows: Tipping Fee* ________/tonne Leachate, gas and monitoring costs ________/tonne Property depreciation ________/tonne Opportunity Costs ________/tonne Total “cost” ________/tonne *Tipping fee: the fee charged to a landfill user for the disposal of a quantity of solid waste. The tipping fee is intended to reflect the costs of land purchase, construction costs, operation and maintenance, and close-out. This is typically considered the “cost” of a landfill. Questions:

1) What are the observed implications of your final Total “cost” figure above? 2) What costs are still not accounted for in this analysis? How might these costs impact

the total “cost”? 3) What you have done today is only half (the C) of a B/C analysis. What might be

factored into a calculation of the B? 4) What are three take home messages from this exercise?

Sources of information:

Much of this assignment came from ideas and text presented in: Heathcote, I.W. 1997. Environmental Problem Solving: a case study approach. McGraw-Hill Company, NY,NY. 197p.

Data provided by: Hirshfeld, S., P.A. Vesilind, and E.I. Pas.1992. Assessing the true cost of landfills. Waste Management and Research. 10(6): 471-484.

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APPENDIX 10

Department of Earth System Science & Policy ESSP 501

Biosphere Productivity Cycle Student Debate Position: Fall 2005

Stewardship as the Last Best Hope for Biodiversity

According to the latest estimates, the extinction rate has accelerated during the past 100 years to about 1,000 times what it was before human civilization developed. It is further estimated that between 1 and 10 percent of all species are extinguished every decade; about 27,000 species a year. Various attempts at slowing or stopping this mass extinction have mostly met with failure. While scientists universally agree that extinction rates are too high and something must be done, convincing policy makers has been far more illusive. In developing countries, for example, where most biodiversity is found, the economic pressures on are so great, people tend to use whatever resources are available making preservation of biodiversity a perceived luxury that generally cannot be afforded.

Environmentalists, on the other hand, have used various arguments to assign

economic value to biodiversity in the attempt to preserve it. These arguments range from identification of the ecosystem services that biodiversity provides to the role it plays as a hedge against disease and famine. Unfortunately, these arguments have not yet convinced policy makers around the world that biodiversity should be preserved for economic reasons. Because scientists know so little of Earth’s biodiversity, let alone what roles species play in the ecosystems they inhabit, it is likely that economics alone will not slow or stop the current mass extinction. A moral argument for the preservation of Earth’s biodiversity may be the last best hope.

Position (Pro side) Stewardship policies that protect biodiversity are the best and probably only option in slowing or stopping the current mass extinction.

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APPENDIX 11


Block I: Materials Cycle Spring 2005

February 7, 2005 Hi all, I would like to give you some feedback on the Full Cost Accounting assignment involving Solid Waste Management and the issue of landfilling waste. First let me tell you what my a priori learning objectives were for this assignment. The full cost accounting assignment, by using solid waste management issues as the platform for discussion, was meant to serve as an example of and brief introduction to the concept of materials cycling. If the ex-post results (in other words what you actually got out of this activity) were significantly different please let me know! Learning Objectives:

1) To examine how materials can cycle through different dimensions. Using solid waste as the example we briefly explored how waste cycles through a socio-environmental complex and the difficulties in examining the multi-dimensional nature (social, environmental, physical, temporal…) of waste within the Life Cycle of a “thing”.

2) To explore the issue of solid waste management by using a method of social accounting called Full Cost Accounting (FCA).

3) To briefly explore how a method such as FCA might fit into the broader economic concepts found in Benefit/Cost analysis.

4) To explore the possible integration of environmental values into a social accounting process – a process that might be called a socio-environmental or socio-ecological analysis.

5) To introduce you to a simple Environmental Impact Matrix Analysis framework – a process that helps organize a more holistic examination and a process that serves as the precursor to a more advanced socio-economic analysis of the issues at hand.

6) To give you an opportunity to examine, organize and use different types of “data” to reach learned conclusions.

Feedback: With regards to the notion of “feedback” there are two main types that educators can provide: summative and formative. Summative feedback is, as the word suggests, a summation of scores. In other words your grade in a quantitative format – a feedback point that typically comes at the end of something, an assignment or a class for example. Formative feedback on the other hand is more qualitative in nature and is designed to evaluate the “process” of learning and is often used to guide and make adjustments while “in stream” so to speak.

1) In summative terms all six of you have scored full points.

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2) In formative terms, I was impressed by a number of things:

a. This was not an easy assignment by any means. The “busy-work” parts of the assignment were not difficult, but in the aggregate I though all of you contributed during the discussions and helped make this an interesting exploration of the multi-dimensionality of this topic. You were capable of “reading between the lines” without any prompting.

b. Despite the data imitations I inadvertently built into the assignment, you were able to make appropriate simplifying assumptions and even make “above and beyond” assumptions that allowed the accounting to be more realistic.

c. All of you contributed in important individual ways as well. Some of you brought into the discussion the oft-neglected philosophical aspects of this topic; some contributed computational prowess; some contributed a tenacity that quickly identified gaps in the data; all contributed components of their personal background to the overall discussion.

d. Kandi and Raj should be commended as they accepted additional work in getting up to speed regarding B/C concepts.

3) Also in formative terms, I was a little disappointed that the final Matrix discussion was dictated a little bit more than it should have been by a desire to be “done” with the assignment. I thought the final matrix – though it generated excellent discussion – was a bit limited (i.e. I though some of your assumptions regarding your directional assessment, particularly the D = depends and ND = no decision, should have been articulated to some degree.)

So far, I am pleased with the process that I am observing.

The final due date is Wednesday the 9th – let me know if this causes any problems!

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APPENDIX 12



Capstone Project




Final Paper:


You must include the following in your paper: 1. A review of the background issues, including a statement of need. 2. A discussion of the objectives of your project with a clear rationale for choosing these

objectives. 3. A clear statement and rationale for your choice of target audience(s). Why these folks? 4. What key questions did you have about your audience(s) and what information did you

gather about your target audience? How did you gather it? What are the strengths and limitations of what you know about them?

5. Clear presentation of your communication strategies. What principles of communication

are you recommending and why? 6. Specific examples - this should include central messages, possible examples of print or

other media. 7. Delineation of how the plan will be evaluated.

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8. Recommendations: how the client can use this information; how future students may build on your work.



References must follow the publication style of the Professional Communication Style

(http://www.ieeepcs.org/activities_publications_transactions_authors.php). Any source which appears in the text must appear in the bibliography.



Personal Statement:



1. Students are expected to take primary responsibility for the development of their

capstone projects. You are expected to conceptualize, carry out, and report your projects. I suggest you formulate your project to help you in your academic career (e.g. thesis chapter, published paper, etc.).



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APPENDIX 13



NON-MARKET VALUATION OF BIODIVERSITY USING NON-TRADITIONAL VALUATION METHODS

To: Northern Great Plains Biosphere Research Group From: Dr. John Tyndall, Assistant Professor of Environmental Policy Dear Research Group: This research request has two main functions: one is to make an effort towards articulating the value of North Dakota’s biodiversity – past and present; the other is to make a “Data-Quality” policy statement regarding the use of various non-traditional socio-cultural economic valuation techniques. As a natural resource economist, I have a scholarly interest in the different ways that economists can qualify and quantify the economic value of something which is relatively nebulous – specifically biodiversity. I am aware of the now conventional methods of non-market environmental valuation, such as contingent valuation, hedonic modeling, travel-cost methods, cost aversion, etc.; however, I also have an interest in non-traditional ways of valuation – at least non-traditional in a neoclassical economic sense. I would like you to, using various methodologies of historians, ethno-botanists, and cultural anthropologists, articulate – qualitatively and, if possible, quantitatively – “traditional values” of North Dakota’s plant, animal, genetic, and ecosystem biodiversity. Specifically (with assistance in identifying these people) I would like you to interview members of key groups of “traditional knowledge keepers” – local historians, indigenous people, mid-20th century (or earlier) farmers. By providing a written recording of various forms of oral history and making a professional appraisal of your experience, specifically I would like you to provide the following:

o A qualitative assessment of the biodiversity “state of affairs” in North Dakota –

provide a historiography perspective. Provide a framework for an economic analysis that can use your data

o Address the issue of bio-prospecting and benefits sharing with regards to ND

o Can non-traditional data collection such as this, provide beneficial insights into

valuation and policy questions? How might one provide “confidence measures” in such data?

We will require a written assessment, formal presentation, and a policy brief (including a script that could be used as a basis for a television information spot). Our highly valued scientific and political advisors, Drs. Hanley, Tyndall, and Laguette will provide you with any

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additional details you might need. Please submit the required materials by the deadlines outlined by Dr. Hanley. Note: a state vehicle or a ride can be provided to you to conduct research. Human Subjects training and approval through IRB will likely be required – no big deal. Also, being a classic technophobe, I request that you are not to use the internet to collect info randomly – perhaps only to look up definitions.

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APPENDIX 14



LAB 2: GIS, AN INTRODUCTION What is a GIS?

In the strictest sense, a GIS is a computer system capable of assembling, storing, manipulating, and displaying geographically referenced information, i.e. data identified according to their locations. Practitioners also regard the total GIS as including operating personnel and the data that go into the system.

Data Source: http://www.usgs.gov/research/gis/title.html How does a GIS work?

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Relating information from different sources

If you could relate information about the rainfall of your State to aerial photographs of your county, you might be able to tell which wetlands dry up at certain times of the year. A GIS, which can use information from many different sources, in many different forms can help with such analyses. The primary requirement for the source data is that the locations for the variables are known. Location may be annotated by x,y, and z coordinates of longitude, latitude, and elevation, or by such systems as ZIP codes or highway mile markers. Any variable that can be located spatially can be fed into a GIS. Federal agencies and private firms are producing several computer databases that can be directly entered into a GIS. Different kinds of data in map form can be entered into a GIS. A GIS can also convert existing digital information, which may not yet be in map form, into forms it can recognize and use. For example, digital satellite images can be analyzed to produce a map like layer of digital information about vegetative covers.

Likewise, census or hydrologic tabular data can be converted to map-like form, serving as layers of thematic information in a GIS.

Data Capture How can a GIS use the information in a map? If the data to be used are not already in digital form, that is, in a form the computer can recognize, various techniques can capture the information. Maps can be digitized, or hand-traced with at computer mouse, to collect the coordinates of features. Electronic scanning devices will also convert map lines and points to digits. A GIS can be used to emphasize the spatial relationships among the objects being mapped. While a computer-aided mapping system may represent a road simply as a line, a GIS may also recognize that road as the border between wetland and urban development, or as the link between Main Street and Blueberry Lane. Data capture - putting the information into the system - is the time-consuming component of GIS work. Identities of the objects on the map must be specified, as well as their spatial relationships. Editing of information that is automatically captured can also be difficult. Electronic scanners record blemishes on a map just as faithfully as they record the map features. For example, a fleck of dirt might connect two lines that should not be connected. Extraneous data must be edited, or removed from the digital data file.

Data integration A GIS makes it possible to link, or integrate, information that is difficult to associate through any other means. Thus, a GIS can use combinations of mapped variables to build and analyze new variables.

Using GIS technology and Water Company billing information, it is possible to simulate the discharge of materials in the septic systems in a neighborhood upstream from a wetland. The bills show how much water is used at each address. The amount of water

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a customer uses will roughly predict the amount of material that will be discharged into the septic systems, so that areas of heavy septic discharge can be located using a GIS.

Projection and registration A property ownership map might be at a different scale from a soil map. Map information in a GIS must be manipulated so that it registers, or fits, with information gathered from other maps. Before the digital data can be analyzed, they may have to undergo other manipulations - projection conversions, for example - that integrate them into a GIS. Projection is a fundamental component of mapmaking. A projection is a mathematical means of transferring information from the Earth's three-dimensional curved surface to a two-dimensional medium - paper or a computer screen. Different projections are used for different types of maps because each projection is particularly appropriate to certain uses. For example, a projection that accurately represents the shapes of the continents will distort their relative sizes. Since much of the information in a GIS comes from existing maps, a GIS use the processing power of the computer to transform digital information, gathered from sources with different projections to a common projection.

Data structures Can a property ownership map be related to a satellite image, a timely indicator of land uses? Yes, but since digital data are collected and stored in various ways, the two data sources may not be entirely compatible. So a GIS must be able to convert data from one structure to another. Image data from a satellite that has been interpreted by a computer to produce a land use map can be "read into" the GIS in raster format. Raster data files consist of rows of uniform cells coded according to data values. An example would be land cover classification.

Raster data files can be manipulated quickly by the computer, but they are often less detailed an may be less visually appealing than vector data files, which can approximate the appearance of more traditional hand-drafted maps. Vector digital data have been captured as points, lines (a series of point coordinates), or areas (shapes bounded by lines). An example of data typically held in a vector file would be the property boundaries for a housing subdivision. Data restructuring can be performed by a GIS to convert data into different formats. For example, a GIS may be used to convert a satellite image map to a vector structure by generating lines around all cells with the same classification, while determining the cell spatial relationships, such as adjacency or inclusion. Thus a GIS can be used to analyze land use information in conjunction with property ownership information.

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Data modeling

It is difficult to relate wetland maps to rainfall amounts recorded at different points such as airports, television stations, and high schools. A GIS, however, can be used to depict two- and three-dimensional characteristics of the Earth's surface, subsurface, and atmosphere from information points. For example, a GIS can quickly generate a map with lines that indicate rainfall amounts.

Such a map can be thought of as a rainfall contour map. Many sophisticated methods can estimate the characteristics of surfaces from a limited number of point measurements. A two-dimensional contour map created from the surface modeling of rainfall point measurements may be overlain and analyzed with any other map in a GIS covering the same area.

What's special about a GIS?

The way maps and other data have been stored or filed as layers of information in a GIS makes it possible to perform complex analyses.

Information retrieval What do you know about the swampy area at the end of your street? With a GIS you can "point" at a location, object, or area on the screen and retrieve recorded information about it from off-screen files.

Using scanned aerial photographs as a visual guide, you can ask a GIS about the geology or hydrology of the area or even about how close a swamp is to end of a street. This kind of analytic function allows you to draw conclusions about the swamp's environmental sensitivity.

Topological modeling In the past 35 years, were there any gas stations or factories operating next to the swamp? Any within two miles and uphill from the swamp? A GIS can recognize and analyze the spatial relationships among mapped phenomena. Conditions of adjacency (what is next to what), containment (what is enclosed by what), and proximity (how close something is to something else) can be determined with a GIS.

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Networks If all the factories near a wetland were accidentally to release chemicals into the river at the same time, how long would it take for a damaging amount of pollutant to enter the wetland reserve? A GIS can simulate the route of materials along a linear network. It is possible to assign values such as direction and speed to the digital stream and "move" the contaminants through the stream system.

Overlay Using maps of wetlands, slopes, streams, land use, and soils, the GIS might produce a new map layer or overlay that ranks the wetlands according to their relative sensitivity to damage from nearby factories or homes.

Data output A critical component of a GIS is its ability to produce graphics on the screen or on paper that convey the results of analysis to the people who make decisions about resources. Wall maps and other graphics can be generated, allowing the viewer to visualize and thereby understand the results of analyses or simulations of potential events.

APPLICATIONS OF GIS Mapmaking

Researchers are working to incorporate the mapmaking experience of traditional cartographers into GIS technology for the automated production of maps. Using a GIS and digital versions of the 1:100,000 - scale transportation network, political boundaries, and hydrographic features, cartographers produced a 1:500,000 - scale standard base map of New Jersey. This digital revision was done in three steps of map scale reduction: 1:100,000, 1:250,000, and 1:500,000.

Each scale reduction required edge matching, or paneling, of the larger scale maps to produce the next small-scale map. In addition, through the process known as generalization, the amount of information was reduced to make the smaller scale map readable.

Site selection The U.S. Geological survey (USGS), in a cooperative project with the Connecticut Department of Natural Resources, digitized more than 40 map layers for the areas covered by the USGS Broad Brook and Ellington 7.5-minute topographic quadrangle maps.

This information can be combined and manipulated in a GIS to address planning and natural resource issues. GIS information was used to locate a potential site for new water well within half a mile of the Somers Water Company service area.

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To prepare the analysis, digital maps of the water service areas were stored in the GIS. Using the buffer function in the GIS, a half-mile zone was drawn around the water company service area. This buffer zone was the "window" used to view and combine the various map coverages relevant to the well site selection. The land use and land cover map for the two areas shows that the area is partly developed. A GIS was used to select undeveloped areas from the land use and land cover map as the first step in finding well sites. The developed areas were eliminated from further consideration. The quality of water in Connecticut streams is closely monitored. Some of the streams in the study area were known to be unusable as drinking water sources. To avoid pulling water from these streams into the wells, 100-meter buffer zones were created around the unsuitable streams using the GIS, and the zones were plotted on the map. The map showing the buffered zone was combined with the land use and land cover map to eliminate areas around unsuitable streams from the analysis. Point sources of pollution are recorded by the Connecticut Department of Natural Resources. hese records consist of a geographic location and a text description of the pollutant. To avoid these toxic areas, a buffer zone of 500 meters was established around each point. This information was combined with the previous two map layers to produce a new map of areas suitable for well sites. The map of surficial geology shows the earth materials that lie above bedrock. Since the area under consideration in Connecticut is covered by glacial deposits, the surface consists largely of sand and gravel, with some glacial till and fine-grained sediments. Of these materials, sand and gravel are the most likely to store water that could be tapped with wells. Areas underlain by sand and gravel were selected from the surficial geology map and combined with the results of the previous selections to produce a new overlay map consisting of sites in undeveloped areas underlain by sand and gravel that are more than 500 meters from point sources of pollution and more than 100 meters from unsuitable streams. A map shows that the thickness of saturated sediments was created by using the GIS to subtract the bedrock elevation from the surface elevation. For this analysis, areas having more than 40 feet of saturated sediments were selected and combined with the previous overlays. The resulting site selection map shows areas that are undeveloped, are situated outside the buffered pollution areas, and are underlain by 40 feet or more of water-saturated sand and gravel. Because of map resolution and the limits of precision in digitizing, the very small polygons (areas) may not have all of the characteristics analyzed, so another GIS function was used to screen out areas smaller than 10 acres. The final six sites are

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displayed with the road and stream network and selected place names for use in the field. The process illustrated by this site selection analysis has been used for a number of common applications, including transportation planning and waste disposal site location. The technique is particularly useful when several physical factors must be considered and integrated over a large area.

Emergency response planning The Wasatch Fault zone runs through Salt Lake City along the foot of the Wasatch Mountains in north-central Utah.

A GIS was used to combine road network and earth science information to analyze the effect of an earthquake on the response time of fire and rescue squads. The area covered by the USGS Sugar House 7.5-minute topographic quadrangle map was selected for the study because it includes both undeveloped areas in the mountains and a portion of Salt Lake City. Detailed earth science information was available for the entire area. The road network from a USGS digital line graph includes information on the types of roads, which range from rough trails to divided highways. The locations of fire stations were plotted on the road network, and a GIS function called network analysis was used to calculate the time necessary for emergency vehicles to travel from the fire stations to different areas of the city. The network analysis function considers tow elements: distance from the fire station, and speed of travel based on road type. The analysis shows that under normal conditions, most of the area within the city will be served in less than 7 minutes and 30 seconds because of the distribution and density of fire stations and the continuous network of roads. The accompanying illustration depicts the blockage of the road network that would result from an earthquake by assuming that any road crossing the fault trace would become impassable. The primary effect on emergency response time would occur in neighborhoods west of the fault trace, where travel times from the fire stations would be lengthened noticeably. The Salt Lake City area lies on lake sediments of varying thicknesses. These sediments range from clay to sand and gravel, and most are water saturated. In an earthquake, these materials may momentarily lose their ability to support surface structures, including roads. The potential for this phenomenon, known as liquefaction, is shown in a composite map portraying the inferred relative stability of the land surface during an earthquake. Areas near the fault and underlain by thick, loosely consolidated, water-saturated sediments will suffer the most intense surface motion during an earthquake. Areas on the mountain front with thin surface sediments will experience less additional ground acceleration. The map of liquefaction potential was combined with the road network analysis to show the additional effect of liquefaction on response times.

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The final map shows that areas near the fault, as well as those underlain by thick, water-saturated sediments, are subject to more road disruptions and slower emergency response than are other areas of the city.

Simulating environmental effects The National Forest Service was offered a land swap by a mining company seeking development rights to a mineral deposit in the Prescott National Forest of Arizona. Using a GIS and a variety of digital maps, the USGS and the Forest Service created perspective views of the area to depict the terrain before and after mining.

Existing digital data were combined in a GIS and displayed using a function that creates perspective drawings. The mining company provided planimetric (two-dimensional) drawings of the proposed mine. This plan was digitized, along with elevation information on the proposed mine and associated piles and ponds. The resulting perspective view illustrates the dramatic changes to the topography that mining would cause. A GIS can combine map types and display them in realistic three-dimensional perspective views that convey information more effectively and to wider audiences than traditional, two-dimensional maps.

Graphic display techniques Traditional maps are abstractions of the real world, a sampling of important elements portrayed on a sheet of paper with symbols to represent physical objects. People who use maps must interpret these symbols. Topographic maps show the shape of land surface with contour lines. The actual shape of the land can be seen only in the mind's eye. Graphic display techniques in GIS's make relationships among map elements visible, heightening one's ability to extract and analyze information. Two types of data were combined in a GIS to produce a perspective view or a portion of San Mateo County, California. The digital elevation model, consisting of surface elevations recorded on a 30-meter horizontal grid, shows high elevations as white and low elevation as black. The accompanying Landsat Thematic Mapper image shows a false-color infrared image of the same area in 30-meter pixels, or picture elements. A GIS was used to register and combine the two images to produce the three-dimensional perspective view looking down the San Andreas Fault.

SOME APPLICATIONS OF GIS AT UMAC Error Analysis for West Nile Virus spread prediction

A map projecting the spread of West Nile Virus (WNV) for the year of 2003 was derived by running Genetic Algorithm for Rule-set Prediction (GARP) model based on the data

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collected in the years 2001 and 2002. The results were checked with the ground truth data for the year 2003 available from The Center for Disease Control (CDC). This error analysis was done using a GIS system. The prediction has been done on a county wide scale. The analysis was based on the containment function of topographic analysis.

Applications in surface runoff calculation

GIS has been used to perform surface runoff modeling and calculations on varied scales here at UMAC. Analysis has been performed from single fields to major watershed areas (Devils lake basin). Running hydrological models would provide values for flow direction, flow accumulation, stream networks, sub-watersheds, etc. The calculations are performed using rigorous multiple iterations based on multiple input layers such as rainfall distribution, topography of the area, groundwater recharge, etc.

These calculations have also been performed for various research projects calculating the water balance equation for different scale geographical regions. The calculations have been used to understand the water cycle in the region and to estimate the water loss due to evaporations and transpiration.

Area of interest (AOI) management and data distribution to end users

The end user community at UMAC mostly comprises of farmers and ranchers and other individuals closely related to the agricultural industry such as insurance agents, etc. All the users are encouraged to decide their AOI and then we make a boundary file for their AOI using x,y coordinates for the four corners. All the data distribution to the end users is done based on their AOIs. Data is clipped to the exact boundary for their AOI so as to reduce the amount of data required to download to the actual size of their AOI. This saves lot of time and band width. AOI management is done using GIS and new AOIs are constantly added for the new end users joining our group.

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LAB ASSIGNMENT: Mapping species richness patterns using ArcView

Introduction

In this lab, we will analyze basic biodiversity data. Specifically, we will look at the spatial distribution of biodiversity data by mapping the country-by country values previously studied.

The purpose of this exercise is to explore a file of biodiversity data to determine patterns of species numbers in space and time. We will be testing hypotheses of the factors determining species richness. In this exercise we will determine some of the large-scale relations between environmental gradients and species richness; at the same time we will be learning how this kind of question can be investigated.

Data and Methods

(1) Import data into ArcView. – The provided file is in CSV (Comma delimited) format suitable for import into ArcView. It was created as follows: Biodiversity Data.xls and saved as a CSV format in Excel. It was then brought into ArcView where it was joined to the world layer, which is an ArcView layer with the countries of the world and their surface area. Incidentally, this was not a straightforward procedure. First I had to ensure the spelling of the various countries was the same, including details such as "Korea PDR" was changed to "Korea, Peoples Democratic Republic". Some countries had changed their names (Burma is now Myanmar, for example), and others missing in one file of the other (ArcView does not have boundaries for many small countries of the world, especially small Islands). Next the data was exported to Excel, where details such as missing data were dealt with. For the purpose of this assignment, Biodiversity Data.csv (see appendix 1) has been updated to match the country names in the "cntry92.shp" file that you will be using for analysis.

Assignment

The assignment is relatively simple, but you will need to think carefully about the data. The first task is to plot the spatial patterns of species richness of mammals, birds, reptiles and amphibians.

(2) Analysis Steps.

a. You need to join the species richness table to a world map in ArcView. Launch ArcView, add a world map to the Table of Contents by clicking on the

“add data” button and navigating to c:/esri/esridata/world/cntry92. Next, you will need to add Table 13-1.csv. This is done the same way as for the

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world layer above. Click on and navigate to Table 13-1.csv and add it to your Table of Contents.

Table Biodiversity Data.csv has been edited to include mammals, birds, reptiles and amphibians normalized by area. This was done in Excel by dividing each value of mammals, birds etc. for each country by the area of the country, and multiplying it by 100,000. This avoided having very small values that are difficult to plot. It is always important to make note of any changes that have been made to the data you are working with.

b. Now, you want to join the information from Table 13-1.csv to the world map layer. Select the cntry92 layer in the Table of Contents and right-click your mouse button. Then, select “Joins and Relates►Join…”. Make sure the information in the dialog box is the same as this:

Here, you are joining the data in Biodiversity Data.csv to the cntry92 layer.

c. Now, right-click on Cntry92, select “Properties” and select the tab “Symbology”. You want to select “Quantities/Graduated Colors”, and under “Value” you will select the appropriate field to answer the questions below (ie.

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mammals, birds, reptiles, amphibians, mamnorm, birdnorm, repnorm, amphnorm).

You will need to be concerned with re-defining the classes of your maps, and this can be done under the Symbology tab in ArcView. On the right hand side of the “Symbology” dialog box there is a box called “Classification”, select

, and the following dialog box appears:

Here you can use the histogram to determine the breaks that appear in your legend, or use the break values on the right.

d. You'll need to account for the countries with missing data. Missing data is represented by a –99 in Biodiversity Data.csv. Therefore, this will show up when you are classifying your data in ArcView. By keeping all negative numbers in one class, you can rename that class in “Symbology” as No Data. Under “Label” simply double-click on the first values in the list and then you are able to type in the label that you want to appear in your Table of Contents. This is also what will show up in your legend. Now you are ready to set up your species diversity maps in layout for printing.

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Questions

Aside from the maps, you should be able to answer ALL questions on one page, single spaced. Double spacing is not required, but if you choose to do so, you are allowed a MAXIMUM of two pages. Also, you should include a couple of sentences for methodology (what software the maps were prepared in; where the data was from – remember, maps are data too; what calculations were performed on the data, etc.).

Make maps of the spatial distribution of biodiversity of mammals, birds, reptiles and amphibians. Are there anomalous values, and why do you think they are there? By anomalous we mean are the results inconsistent or deviating from what would be expected. Think about these questions and comment, where necessary for questions 1 and 2. DO NOT turn these maps in.

(1) Create a choropleth map of the data normalized by area. Make maps of the spatial distribution of biodiversity of mammals, birds, reptiles and amphibians. This should be done in layout view. These maps should be turned in, so prepare them accordingly (Please include all components that you see on professional maps): (5 pts.)

• What are the spatial patterns of biodiversity (describe the patterns on the maps)? (3 pts.)

• Do the 4 groups of vertebrates show similar patterns? (1 pt.)

(2) What can we learn from these data, and what are problems with our analysis (and perhaps our conclusion)? First, keep in mind the data. Since biodiversity is a scale dependent phenomenon, it is a bit problematic to compare data from large countries such as the USSR (former Soviet Union) or Canada with small countries such as Monaco or Guam. Normalizing the data by area helped, but it must be easier to get an accurate count in small countries than large ones. (3 pts.)

(3) What other problems are there with these data? Then think about the quality of the

data. Where are the missing data? These data have been compiled from many sources and have been collected over the past two centuries, although the pace of scientific research has accelerated in more recent decades. Where are the better collections? You can perhaps understand if there are no data from Angola, where there has been a war going on for decades, and where there are millions of land mines scattered through the landscape. (3 pts.)

(4) Are there other such areas where you can reasonably explain these data? (3 pts.)

(5) Are data missing from countries where you would suspect there should be good data? (2 pts.)

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Appendix 1. Country-by-country list of the total number of species (species richness) of mammals, birds, reptiles, and amphibians.

COUNTRY AREA MAMMAL BIRD REPTILES AMPHIBIANS MAMNORM BIRDNORM REPNORM AMPHNORM

Afghanistan 249503 123 456 103 6 49.3 182.76 41.28 2.4

Albania 10772 68 215 31 13 27.25 86.17 12.42 5.21

Algeria 891693 92 192 -99 -99 36.87 76.95 -99 -99

Angola 476840 276 872 -99 -99 110.62 349.49 -99 -99

Antarctica 4718827 -99 -99 0 0 -99 -99 0 0

Argentina 1071584 258 -99 -99 123 103.41 -99 -99 49.3

Australia 2958532 282 571 700 180 113.02 228.85 280.56 72.14

Austria 32782 83 227 14 20 33.27 90.98 5.61 8.02

Bangladesh 52466 109 354 119 19 43.69 141.88 47.69 7.62

Belgium 12092 58 180 8 17 23.25 72.14 3.21 6.81

Belize 8543 125 528 107 -99 50.1 211.62 42.89 -99

Benin 44805 188 630 -99 -99 75.35 252.5 -99 -99

Bhutan 14789 109 448 19 24 43.69 179.56 7.62 9.62

Bolivia 421161 280 1257 250 110 112.22 503.8 100.2 44.09

Botswana 227569 154 569 143 36 61.72 228.05 57.31 14.43

Brazil 3251214 394 1573 468 502 157.91 630.45 187.57 201.2

Brunei 2600 155 359 44 76 62.12 143.89 17.64 30.46

Bulgaria 46115 81 242 33 17 32.46 96.99 13.23 6.81

Burkina Faso 106765 147 497 -99 -99 58.92 199.2 -99 -99

Burma 253446 300 867 203 75 120.24 347.49 81.36 30.06

Burundi 10923 107 633 -99 -99 42.89 253.7 -99 -99

Cambodia 70393 117 305 82 28 46.89 122.24 32.87 11.22

Cameroon 178767 297 848 -99 -99 119.04 339.88 -99 -99

Canada 3702824 139 426 41 40 55.71 170.74 16.43 16.03

Central African Republic 243895 209 668 -99 -99 83.77 267.73 -99 -99

Chad 489736 134 496 -99 -99 53.71 198.8 -99 -99

Chile 258251 91 432 78 29 36.47 173.14 31.26 11.62

China 3607953 394 1100 282 190 157.91 440.88 113.02 76.15

Colombia 445382 359 1721 383 407 143.89 689.77 153.51 163.12

Congo 127092 200 500 -99 -99 80.16 200.4 -99 -99

Costa Rica 19508 205 848 214 162 82.16 339.88 85.77 64.93

Cuba 38776 31 159 100 41 12.42 63.73 40.08 16.43

Cyprus 3545 21 80 23 4 8.42 32.06 9.22 1.6

Czechoslovakia 49424 81 277 12 19 32.46 111.02 4.81 7.62

Denmark 12513 43 185 5 14 17.23 74.15 2 5.61

Djibouti 8304 -99 311 -99 -99 -99 124.65 -99 -99

Dominican Republic 17512 20 125 -99 -99 8.02 50.1 -99 -99

Ecuador 96025 271 1435 337 343 108.62 575.14 135.07 137.47

Egypt 386286 102 132 83 6 40.88 52.91 33.27 2.4

El Salvador 8064 135 450 73 23 54.11 180.36 29.26 9.22

Equatorial Guinea 9510 184 392 -99 -99 73.75 157.11 -99 -99

Estonia 14959 -99 -99 -99 -99 -99 -99 -99 -99

Ethiopia 488139 255 836 -99 -99 102.2 335.07 -99 -99

Finland 128771 60 230 5 5 24.05 92.18 2 2

France 212659 93 267 32 32 37.27 107.01 12.83 12.83

French Guiana 31921 152 -99 -99 -99 60.92 -99 -99 -99

Gabon 98838 190 617 -99 -99 76.15 247.29 -99 -99

Gambia, The 3866 108 489 -99 -99 43.29 195.99 -99 -99

Germany 135096 76 237 12 20 30.46 94.99 4.81 8.02

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Ghana 90933 222 721 -99 -99 88.98 288.97 -99 -99

Greece 40595 95 244 51 15 38.08 97.79 20.44 6.01

Greenland 806568 -99 -99 -99 -99 -99 -99 -99 -99

Guatemala 41860 184 480 231 88 73.75 192.38 92.58 35.27

Guinea 98002 190 529 -99 -99 76.15 212.02 -99 -99

Guinea-Bissau 10898 108 376 -99 -99 43.29 150.7 -99 -99

Guyana 81006 193 -99 -99 -99 77.35 -99 -99 -99

Haiti 9916 20 -99 -99 -99 8.02 -99 -99 -99

Honduras 43710 173 -99 152 56 69.34 -99 60.92 22.44

Hungary 36899 72 203 15 17 28.86 81.36 6.01 6.81

Iceland 38755 11 80 0 0 4.41 32.06 0 0

India 1216700 317 969 389 206 127.05 388.37 155.91 82.56

Indonesia 655358 515 1519 511 270 206.41 608.81 204.81 108.22

Iran 623447 140 -99 164 11 56.11 -99 65.73 4.41

Iraq 170324 81 145 81 6 32.46 58.12 32.46 2.4

Ireland 26184 25 141 1 3 10.02 56.51 0.4 1.2

Israel 12021 -99 169 -99 -99 -99 67.73 -99 -99

Italy 114335 90 254 40 34 36.07 101.8 16.03 13.63

Ivory Coast 121068 -99 -99 -99 -99 -99 -99 -99 -99

Jamaica 3489 22 159 -99 -99 8.82 63.73 -99 -99

Japan 138363 90 250 63 52 36.07 100.2 25.25 20.84

Jordan 34564 -99 132 -99 -99 -99 52.91 -99 -99

Kenya 230614 309 1067 187 88 123.85 427.65 74.95 35.27

Korea, Republic of 35253 -99 -99 19 13 -99 -99 7.62 5.21 Korea, Democratic People's Republic of 49019 49 -99 18 13 19.64 -99 7.21 5.21

Kuwait 6229 -99 27 29 2 -99 10.82 11.62 0.8

Laos 89239 173 481 66 37 69.34 192.78 26.45 14.83

Latvia 24074 -99 -99 -99 -99 -99 -99 -99 -99

Lebanon 3959 52 124 -99 -99 20.84 49.7 -99 -99

Lesotho 11756 33 288 -99 -99 13.23 115.43 -99 -99

Liberia 35152 193 590 62 38 77.35 236.47 24.85 15.23

Libya 624835 76 80 -99 -99 30.46 32.06 -99 -99

Lithuania 25020 -99 -99 -99 -99 -99 -99 -99 -99

Luxembourg 1041 55 130 7 14 22.04 52.1 2.81 5.61

Madagascar 223560 105 250 252 144 42.08 100.2 101 57.71

Malawi 42840 195 630 134 69 78.16 252.5 53.71 27.65

Malaysia 124769 264 501 268 158 105.81 200.8 107.41 63.33

Mali 482377 137 647 16 -99 54.91 259.32 6.41 -99

Mauritania 394924 61 59 -99 -99 24.45 23.65 -99 -99

Mexico 742519 439 961 717 284 175.95 385.17 287.37 113.83

Mongolia 601706 -99 -99 -99 -99 -99 -99 -99 -99

Morocco 158870 105 209 -99 -99 42.08 83.77 -99 -99

Mozambique 301573 179 666 -99 62 71.74 266.93 -99 24.85

Namibia 309843 154 640 -99 32 61.72 256.51 -99 12.83

Nepal 56912 167 629 80 36 66.93 252.1 32.06 14.43

Netherlands 12735 55 187 7 16 22.04 74.95 2.81 6.41

New Zealand 96141 -99 285 40 3 -99 114.23 16.03 1.2

Nicaragua 47031 -99 -99 161 59 -99 -99 64.53 23.65

Niger 456457 131 473 -99 -99 52.5 189.58 -99 -99

Nigeria 350733 274 831 100 60 109.82 333.06 40.08 24.05

Norway 134944 54 235 5 5 21.64 94.19 2 2

Oman 119470 46 -99 64 -99 18.44 -99 25.65 -99

Pakistan 336399 151 476 143 17 60.52 190.78 57.31 6.81

Panama 28310 218 922 226 164 87.37 369.53 90.58 65.73

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Papua New Guinea 163275 242 578 249 183 96.99 231.66 99.8 73.35

Paraguay 155574 156 650 120 85 62.52 260.52 48.1 34.07

Peru 503049 344 1705 298 241 137.87 683.36 119.44 96.59

Philippines 89642 166 395 193 63 66.53 158.31 77.35 25.25

Poland 118022 85 224 9 18 34.07 89.78 3.61 7.21

Portugal 35947 63 214 29 17 25.25 85.77 11.62 6.81

Puerto Rico 3072 13 94 46 22 5.21 37.67 18.44 8.82

Qatar 3901 -99 -99 17 -99 -99 -99 6.81 -99

Romania 89444 84 249 25 19 33.67 99.8 10.02 7.62

Rwanda 10534 151 669 -99 -99 60.52 268.13 -99 -99

Saudi Arabia 738518 -99 59 84 -99 -99 23.65 33.67 -99

Senegal 81582 155 625 -99 -99 62.12 250.5 -99 -99

Sierra Leone 26679 147 614 -99 -99 58.92 246.09 -99 -99

Somalia 246958 171 639 193 27 68.54 256.11 77.35 10.82

South Africa 473525 247 774 299 95 99 310.22 119.84 38.08

Spain 187441 82 275 53 25 32.87 110.22 21.24 10.02

Sri Lanka 23921 86 221 144 39 34.47 88.58 57.71 15.63

Sudan 968058 267 938 -99 -99 107.01 375.95 -99 -99

Suriname 57722 187 -99 -99 -99 74.95 -99 -99 -99

Swaziland 6635 47 381 109 39 18.84 152.7 43.69 15.63

Sweden 167420 60 249 6 13 24.05 99.8 2.4 5.21

Switzerland 16005 75 201 14 18 30.06 80.56 5.61 7.21

Syria 74889 -99 165 -99 -99 -99 66.13 -99 -99

Taiwan 12711 62 160 67 26 24.85 64.13 26.85 10.42

Tanzania, United Republic of 364692 306 1016 245 121 122.64 407.21 98.2 48.5

Thailand 195367 251 616 298 107 100.6 246.89 119.44 42.89

Togo 23281 196 630 -99 -99 78.56 252.5 -99 -99

Trinidad 1875 100 258 -99 -99 40.08 103.41 -99 -99

Tunisia 59940 78 173 -99 -99 31.26 69.34 -99 -99

Turkey 305181 116 284 102 18 46.49 113.83 40.88 7.21

Uganda 92854 315 989 119 44 126.25 396.39 47.69 17.64

Union of Soviet Socialist Republics 8326645 276 -99 168 37 110.62 -99 67.33 14.83

United Arab Emirates 39606 -99 -99 37 -99 -99 -99 14.83 -99

United Kingdom 84610 50 219 8 7 20.04 87.77 3.21 2.81

United States 3629625 349 650 -99 -99 139.88 260.52 -99 -99

Uruguay 67750 81 -99 -99 -99 32.46 -99 -99 -99

Venezuela 358883 288 1308 -99 -99 115.43 524.24 -99 -99

Vietnam 128636 273 638 180 80 109.42 255.71 72.14 32.06

Western Sahara 102597 15 60 -99 -99 6.01 24.05 -99 -99

Yemen 151110 -99 -99 77 -99 -99 -99 30.86 -99

Yugoslavia 97833 95 245 41 23 38.08 98.2 16.43 9.22

Zaire 905921 415 1086 -99 -99 166.33 435.27 -99 -99

Zambia 293554 229 732 -99 83 91.78 293.38 -99 33.27

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APPENDIX 15 Lab # 4 Advanced GIS Applications Lab The goal: create new layer of information based on known information and according to specific

rules.

1. The ERDAS Imagine Model Maker

2. Tool Box

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3. Insert raster file

4. Insert vector file

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5. Operations among spatial files

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6. Writing model to determine the class for each pixel.

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7. The resulted raster

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Lab # 5

The goal: Preparing a map for printing. The items that should be include in print out map: 1. Legend; Scale bar (not scale text !); North arrow; Location map or coordinate grid net. 2. Title (some time in the document and not in the map itself, could be just a title and could be title plus exploitation), Reference or source; Places or important locations as reference.

Switch to map view instead of data view. a. Insert = > Legend b. Insert = > Scale bar c. Insert = > North Arrow d. Map properties (right click on the mouse when highlight the map) => Grid e. Insert = > Text or text icon in the Draw menu

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APPENDIX 16



Assignment #3: Op-Art of Environmental-Related Graphic or Advertisement

Your assignment is to select an environmental-related graphic or advertisement from a

newspaper, magazine, or website. This can be essentially any environmental-related graphic or ad you would like; however, it should fit on one page. Using this graphic or ad, you will produce an op-art piece that explains the communication mechanisms, successes, failures, or other interesting communication points. For example:

What message(s) is the text attempting to communicate? Can you identify the intent of the text?

Who or what is the target audience of the text? Using some model of communication, what assumptions is the sender making about the

receiver? Is there a feedback mechanism? What messages (if any) does it communicate about nature or ecosystems? What techniques or strategies does it use? In your estimation, how effective is it?

By op-art piece, I am referring to an opinion piece like the one shown below originally published in

the New York Times. I am not referring to art movement of the 1960s that exploited the fallibility of the eye through the use of optical illusions.

Palm Beach County Ballot, 2000 Presidential Election

Bush is first on the ballot, and the punch dot for the Republicans Is also first. This is a good design, making it highly unlikely that a Bush voter would make an error.

The Democrats are listed second, but the correct punch dot for them is third. Since it islogical to assume that one punches the second dot on the ballot to vote for them, this is an

f l d i

Arrows look decorative, not

Since the English language is read from left to right, it is natural to expect that the dot will appear after the name. The sudden shift in the pattern – putting the Dots for the right column on the left – is likely to confuse voters

This is the logical place for the dots corresponding to the second column of party Listings. (Florida law actually specifies that voters must mark the box to the right of the ballot. The county election officials foolishly violated this law.)

** Many official bodies and corporations approve products or documents thatare incompletely designed. When a design causes problems for a significantnumber of people, even if it was “approved,” the product is usually recalled, and sometimes reparations are made.

Modified from New York Times (11/14/2000), Paula Scher, Op-Art

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The example above is of one style that could be used. You are free to use whatever style you would like that addresses the communication mechanisms, successes, failures, or other interesting communication points.

Your op-art piece should be printed within 36” by 48” and include the original graphic or

advertisement (scanned). You will be free to use the color poster printer in the ESSP geospatial lab to print out your piece. This assignment is due on October 20, 2005 in class. During this class, you will briefly describe your op-art piece (~5-10 minutes only) and field any questions.

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APPENDIX 17



NATURE-BASED TOURISM IN THE PEMBINA GORGE, NORTH DAKOTA To: Northern Great Plains Biosphere Research Group From: North Dakota Parks and Recreation Department Dear Research Group:

On Friday August 20, 2004, Gov. John Hoeven announced that the state will help fund a trails planning study of the Pembina Gorge area. This study is a step in a process that was started in 2002 to develop nature-based tourism in the state. “Pembina Gorge is a treasure on North Dakota’s landscape, and we need to find ways to make them more accessible to all,” Hoeven said. We are pleased to announce that your organization has been awarded the cooperative agreement to carry out this study.

Specifically, the North Dakota Parks and Recreation Department needs the

following:

• An inventory of existing trails • Identify corridors for potential trail systems, keeping in mind cultural, historical,

and archaeological features of the region • A generalized environmental risk assessment for the proposed corridors • Estimate potential recreational demand • Determine potential carrying capacity for recreational use • Benefit cost analysis based on estimated demand figures

We want to minimize the impact of the proposed areas as much as possible,

while at the same time giving people an opportunity to see areas of interest. Please consider all types of trails, including walking, hiking, biking, horseback riding, water, and all-terrain vehicles.

We will require a written recommendation, formal presentation, and a policy brief

(including a script that could be used as a basis for a television information spot). Our highly valued scientific and political advisors, Drs. Hanley, Tyndall, and Laguette will provide you with any additional details you might need. Please submit the required materials by the deadlines outlined by Dr. Hanley.

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APPENDIX 18



News from the University of North Dakota Office of Communications 22 Twombly hall. Grand Forks, ND 58201 Telephone 777.777.7777; Fax 777.777.7778

For immediate release: May 27, 2004 Media contact: Thomas J. Hobbes, (609) 258-5729, [email protected]

Media advisory: Climate experts can comment on 'Day After Tomorrow' UND scientists can help separate fact from fiction in new film

(Grand Forks, ND) The University of North Dakota is home to leading climate scientists who are available to comment on the upcoming summer movie "The Day After Tomorrow" and its portrayal of human-induced global climate change.

The film, which will be released May 28, 2004 presents an apocalyptic scenario of sudden climate change brought on by global warming. Much like how Michael Crichton’s 1992 blockbuster Jurassic Park sparked discussion between the scientific community and the general public regarding genetic cloning, this film is expected to generate the same furor in the context of global climate change. UND’s ESSP 502 class is listed among the scientists who will help distinguish between established scientific conclusions and the fictionalized aspects of the film. In preparation of meeting with the public in a Q & A forum which will take place in the UND MU Grand Hall on May 30, all participating scientists are invited to a pre-release screening beginning at 9 AM in room 220, Clifford Hall.

#### Lab Assignment: Your task is to identify the climate change scenarios (ramifications) portrayed in the film (as many as you can) - even when the film makers are taking some “creative” liberties with scientific understanding.

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In teams of 2, organize the information requested in tasks 1-4; prepare for task 5:

1) Briefly describe the scenario/ramification and its scientific premise as portrayed in the film.

2) Outline any flaws in the science within each of your identified scenarios above.

3) Describe the likely (or hypothesized) reality of each identified scenario based on current scientific evidence –be prepared to show evidence from the scientific literature (you may define “show” as you wish).

4) Answer the following question: Is this fictionalized account of complex environmental issues a good platform to discuss scientific issues with the general public?

5) Be as prepared as possible to face an audience of the general public for a Q & A session regarding issues brought up in the movie and global climate change in general. This will occur during the normal lab hours. This is going to be rather informal.

Each 2 person team is to turn in a paper copy of their responses to tasks 1-4 no later than March 30 (Note: think of this assignment as helping you study for your quiz). This lab assignment is worth 25 points. Since this lab is intended to be both fun and informative the emphasis on the grading will be on your ability to concisely and clearly articulate your responses, not on your ability to be comprehensive and exhaustive. Discuss at least three scenarios/ramifications in your replies to tasks 1-3. Cite all sources used. During the Q & A portion of this lab, which will take place during your lab hours, all of you are expected to participate in the answering of the questions posed by your audience. To ensure equal opportunity for full student panel participation, the moderator will allow ample opportunity for full student participation in the answering of a question. For example, if one member of your panel takes the initiative to answer a particular question directly, feel encouraged to add to the discussion by offering your own scientific or philosophical “2¢” to the discussion – i.e. introduce new examples, introduce additional or new scientific, social or philosophical dimensions of the question not discussed. However, be prepared to be called upon by name. Learning Objectives:

• Experience and gain insights into a significant socio-environmental phenomenon: That is, the majority of our society (including many policy-makers) largely achieves understanding of environmental science and environmental issues through an assortment of both popular culture and media outlets (the internet is a major component of this dynamic) all with highly variable levels of “information quality”. An outcome of this social dynamic is that many discussions (and policies) in the environmental “arena” often revolve around half-truths, distortions, spurious correlations, agenda based points of view, and false or weak premises. Examples of the outcomes of this state of affairs are perhaps seen in the general societal disinterest (or worse, distrust) in environmental issues and in the politicization of science.

• Further expand our exploration of global environmental change. As always, if any of these objectives are not satisfactorily met please let us know!

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APPENDIX 19 Lab # 6 Advanced GIS Measurement Lab Creating buffer to map distance from land-use or landmark. Data available for this project are in: P:\ESSP_Public\Materials Block\Grand Forks GIS data The buffer command in GIS is useful to find area around a point, line or polygon. For example, in case of landfill allocation, it allows to map the entire area that is less than 2 mile from a road. Combination of two, or more, buffer maps could help to find a site that fit to two different conditions: buffer from roads and buffer from drainage network could reveal where the areas that are nearby roads but faraway from water. The buffer commands in ArcGIS 9 – there are two options, both in ArcToolbox: (1) Buffer (analysis) and (2) Multiple Ring Buffer. Open ArcToolbox and search for the buffer command by typing that name.

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The Buffer (analysis) command allow us to determine the buffer distance according to a linear distance (depends on the units the user is using) or a variable depended units, which relate higher distance to greater values.

The Multiple Ring Buffer command allows us to create different buffers:

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Combining the buffer layers will be with the “Union” command:

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Creating new variable with different values for each buffer area – the new Field will be added in the attribute table by right click of the mouse. The values will be zeros and they can be changed after activating the “start editing” from the Editor menu.

The new variable values could also be calculated from current variables

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The assignment is to find where in the AOI shape file, we can allocate landfill according to three layers: places, hydrology (rivers) and roads. You need to write a report that present your findings and explain the definition for each one of the variables that you use. The report is due to Wednesday, Feb. 2.

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APPENDIX 20


Block II: Biosphere’s Productivity Cycle-Dr. Hanley Student Led Discussion Evaluation: Fall 2005

Student: Paper: Grading Matrix for Student-Led Discussion 50 points possible

Criteria Max. pts. Your pts. Description of paper

• What’s the overall context/goal? • What is the question/hypothesis? • How is it evaluated?

15

Comments

Analysis of the information presented • Do the experiments/analysis address the

question? • Are the answers clear?

15

Comments

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Evaluation of conclusions • Are the conclusions justified? • How did this study advance the field? • What are the societal impacts or policy

implications, if any?

10

Comments

Organization and effectiveness of discussion • Logically orientated • Student participation

10

Comments

Overall Comments

Total Points

Possible 50

Score

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APPENDIX 21



Building bridges: the purpose of Earth system science

An example with the water cycle The water cycle can be understood as an open system regulated by its inputs and outputs. Every reservoir in the system is connected to the other reservoirs by fluxes. Each reservoir of the hydrologic system however is also part of other systems such as the atmosphere or the biosphere. Variations of some reservoirs parameters, such as temperature, concentration of elements (CO2, N2, etc.), and land use changes can induce changes in the systems’ balance, provoking cascade changes over the whole Earth System.

Nonetheless this scenario as articulated above is almost entirely focused on Earth science with seemingly little to do with the human component of this “system”. Yet, we have approached the water system from another perspective (albeit in a very brief and micro-costic way): socio-hydrologic cycling. Changes (such as fluxes and cascading effects) can be due to natural phenomena but change can also be induced by human activities, and changes (again fluxes and cascading effects) are manifest in

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many interrelated dimensions (biologic, hydrologic, geologic, sociologic – which includes the economic and the political, across time and space…).

What are the bridges linking the scientific aspect of the water system with this human, economical aspect? Your task is to concisely articulate (in an effective way of your choice) an example “bridge”.

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APPENDIX 22 Material Block: Movement of crop material from one year to another Assignment 5 – Mapping Nitrogen (N) credit for the Red River Valley The goal of this project is to prepare a method for UMAC N credit product. This product should map N credit on a large scale, in order to help end users to reduce their fertilization without affecting the yield. There are also environmental issues relating this product and it should include public awareness and education. Most of the research in the RRV is conducted on assessing sugar beet N credit, while other crops do not have much attention. As part of the Material block, the project should emphasize how to use current methods, to estimate N credit from the main crops in the valley. The main focal points are: • The importance of the N credit method for sustainability and how we can assess it • Differences among crops in the N credit importance, • How to assess N credit with remote sensing, • How to validate the product accuracy, and • How to create a friendly-user-product and assess it.

The results should be present by a short presentation (Tuesday, Feb 15th) and a paper (Wednesday, Feb 16th). The presentation should lead to discussion. Team: 3 members. Thursday – introduction to the sugar beet crop and the crop rotation. Friday – paper discussion, representing the main focal points. Monday – personal meeting with each group. Tuesday – presentation. Wednesday – paper submission. Thursday, Friday and Tuesday meetings at 9 a.m., room 220 Monday and Wednesday meetings at 9 a.m., room 310 (or 316)

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Papers: A. crop rotation and crop cycling –

Vos, J. and P. E. L. van der Putten (2000). "Nutrient cycling in a cropping system with potato, spring wheat, sugar beet, oats and nitrogen catch crops. I. Input and offtake of nitrogen, phosphorus and potassium." Nutrient Cycling in Agroecosystems 56: 87-97.

Franzen, D. W., J. F. Giles, L. J. Reitmeier, A. J. Hapka, A. J. Hapka, N. R. Cattanach and A. C. Cattanach (2001). "Summary of four years of research on poor quality sugarbeets in a sugarbeet, spring wheat, potato rotation." Sugarbeet Research and Extension Reports 32: 152-173.

Hapka, A. J., D. W. Franzen, J. F. Giles and N. R. Cattanach (2000). "Timing and release of nitrogen from residues." Sugarbeet Research and Extension Reports 31: 114-121.

Moraghan, J. T. and L. J. Smith (1996). "Nitrogen in sugarbeet tops and the growth of a subsequent wheat crop", Agronomy Journal 88: 521-526.

B. remote estimation of sugar beet N credit Sims, A.L., J. T. Moraghan and L. Smith (2002). "Spring wheat response to fertilizer

nitrogen following a sugarbeet crop varying in canopy color." Precision Agriculture 3: 283-295.

Franzen, D. W., G. Wagner and A. Sims (2003), ”Application of a ground-based sensor to determine N credit from sugar beet”, Sugarbeet Research and Extension Reports 34. 119-123

Johnson, K.L., T. M. Leshuk, D. R. Bernhardson and A. W. Cattanach (2001), “Variable rate N application on wheat after sugarbeet – “putting research into practice”, Sugarbeet Research and Extension Reports 32. 116-120

Suggested points for discussion, Vas and van der Putten: • The introduction: the policy behind the research • Definition for nutrient balance • What are the research findings about each one of the crops and their capability for N credit? Suggested points for discussion, Sims, Moraghan and Smith: • The use of aerial photography: can it be applied to a large scale as the RRV? • What is the use of the remote sensing in this research? Is this method allowing quantifying of

N credit or can it be used for relative zones-mapping inside a field? • Can this research approach be used for remote sensing product evaluation?

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Good source on sugar beet in the RRV can be found in the Sugarbeet Research & Education Board. They conducting an annual conference, which is summarize in research reports:

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APPENDIX 23



Assignment #4: Letter to the Editor

Letters to the editor of newspapers are an excellent means for commenting on environmental issues and making a point about a particular issue. Letters from readers have been shown to be one of the most widely read sections of newspapers, and have the potential of reaching particularly large audiences. They also have the ability to influence readers in ways regular articles in the newspaper cannot and help move or set a community agenda. In fact, President Clinton once remarked that his reelection campaign in 1996 was crafted by reading letters to the editor of newspapers around the country.

Your assignment is to write a letter to the editor of a newspaper (local-Grand

Forks Herald, or national-New York Times) dealing with your final project. This letter can advocate a particular position from your project or draw attention to a particular problem or issue. Specifically, you should comment on the communication aspects of the issue you choose. As usual, your letter will be graded based on the quality of the background information, description of the message, context of the message, and overall organization of the letter. Your letter should be brief and to the point and adhere to the length requirements of the newspaper for which you choose to write.

Your letter will be due on November 10. In that class, you will give a brief presentation of your letter (≤10 minutes in length).

After your letter is graded and editorial suggestions are provided, you will have

one week to submit it for publication in the newspaper of your choice. If you choose to submit it for publication and you provide evidence of the submission, you will receive an additional 5 points extra credit.

departmental plan for assessment of student learning€¦ · 2007-10-20 · these update of the...

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